Evidence map›Paper›PMID 39574678›Full record

ArticlebioRxiv : the preprint server for biology2024

Population size interacts with reproductive longevity to shape the germline mutation rate.

Luke Zhu, Annabel Beichman, Kelley Harris

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Luke ZhuDepartment of Bioengineering, University of Washington.ORCID 0000-0002-6324-1464
Annabel BeichmanDepartment of Genome Sciences, University of Washington.ORCID 0000-0002-6991-587X
Kelley HarrisDepartment of Genome Sciences, University of Washington.ORCID 0000-0003-0302-2523

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

Mutation rates vary across the tree of life by many orders of magnitude, with lower mutation rates in species that reproduce quickly and maintain large effective population sizes. A compelling explanation for this trend is that large effective population sizes facilitate selection against weakly deleterious "mutator alleles" such as variants that interfere with the molecular efficacy of DNA repair. However, in multicellular organisms, the relationship of the mutation rate to DNA repair efficacy is complicated by variation in reproductive age. Long generation times leave more time for mutations to accrue each generation, and late reproduction likely amplifies the fitness consequences of any DNA repair defect that creates extra mutations in the sperm or eggs. Here, we present theoretical and empirical evidence that a long generation time amplifies the strength of selection for low mutation rates in the spermatocytes and oocytes. This leads to the counterintuitive prediction that the species with the highest germline mutation rates per generation are also the species with most effective mechanisms for DNA proofreading and repair in their germ cells. In contrast, species with different generation times accumulate similar mutation loads during embryonic development. Our results parallel recent findings that the longest-lived species have the lowest mutation rates in adult somatic tissues, potentially due to selection to keep the lifetime mutation load below a harmful threshold.

Indexed as

Biological Scienceseffective population sizeEvolutiongeneration timeMutation ratemutator allelenearly neutral theory

Identifiers

PMID39574678
PMCPMC11580940

What OpenQuestion holds

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LicenceCC BY
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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.