Evidence map›Paper›PMID 38669515›Full record

ReviewAnnual review of biomedical data science2024

The Evolutionary Interplay of Somatic and Germline Mutation Rates.

Annabel C Beichman, Luke Zhu, Kelley Harris

Abstract readReview
In one paragraph

Review in Annual review of biomedical data science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. What sets the mutation rate of a cell type in an animal species?bioRxiv : the preprint server for biology · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Characterizing the rates and patterns ofbioRxiv : the preprint server for biology · 2024
    Article
  14. 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

3 authors.

Annabel C BeichmanDepartment of Genome Sciences, University of Washington, Seattle, Washington, USA; email: harriske@uw.edu.
Luke ZhuDepartment of Bioengineering, University of Washington, Seattle, Washington, USA.
Kelley HarrisComputational Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA.

Funding

Biological Mechanisms of Healthy Aging Training GrantT32AG066574 · NIA · UNIVERSITY OF WASHINGTON · PI David J. Marcinek, Jessica E Young · 2020 to 2026
$5.3M
Investigating the landscape and genetic architecture of germline mutagenesisR35GM133428 · NIGMS · UNIVERSITY OF WASHINGTON · PI Kelley Harris · 2019 to 2026
$2.8M
NIA NIH HHS T32 AG066574NIGMS NIH HHS R35 GM133428
6 · The paper itself

Abstract

Novel sequencing technologies are making it increasingly possible to measure the mutation rates of somatic cell lineages. Accurate germline mutation rate measurement technologies have also been available for a decade, making it possible to assess how this fundamental evolutionary parameter varies across the tree of life. Here, we review some classical theories about germline and somatic mutation rate evolution that were formulated using principles of population genetics and the biology of aging and cancer. We find that somatic mutation rate measurements, while still limited in phylogenetic diversity, seem consistent with the theory that selection to preserve the soma is proportional to life span. However, germline and somatic theories make conflicting predictions regarding which species should have the most accurate DNA repair. Resolving this conflict will require carefully measuring how mutation rates scale with time and cell division and achieving a better understanding of mutation rate pleiotropy among cell types.

Indexed as

Germ-Line MutationMutation RateAnimalsEvolution, MolecularGerm CellsHumansMutationNeoplasmsagingdrift-barrier hypothesiseffective population sizegermline mutationmutator allelePeto's paradoxsomatic mutation

Identifiers

PMID38669515
PMCPMC12254932

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Registered trials

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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.