Evidence map›Paper›PMID 42779615›Full record

ArticlebioRxiv : the preprint server for biology2026

Dynamics of mutators of arbitrary dominance in humans.

Matin Saeidi, Guy Sella, Molly Przeworski, William Milligan

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

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

4 authors.

Matin SaeidiDepartment of Biological Sciences, Columbia University, New York, USA.ORCID 0009-0003-1802-9004
Guy SellaDepartment of Biological Sciences, Columbia University, New York, USA.ORCID 0000-0002-5239-7930
Molly PrzeworskiDepartment of Biological Sciences, Columbia University, New York, USA.ORCID 0000-0002-5369-9009
William MilliganDepartment of Biological Sciences, Columbia University, New York, USA.ORCID 0000-0002-2836-5402

Funding

The population genetics of disease risk and other quantitative traitsR01GM115889 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI SELLA, GUY · 2015 to 2025
$2.9M
Mechanisms of mutation and recombination and their evolution in vertebratesR35GM153355 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI MOLLY F PRZEWORSKI · 2024 to 2026
$1.0M
Reconciling observations from human genetics and phylogenetics: an integrated approach to the study of mutationF32GM163397 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI William Robert Milligan · 2026 to 2026
$79k
NIGMS NIH HHS F32 GM163397NIGMS NIH HHS R01 GM115889NIGMS NIH HHS R35 GM153355
6 · The paper itself

Abstract

Recent findings in humans and other species have revealed the presence of "mutator" alleles that increase germline mutation rate across the genome. Such mutators are expected to be selected against because of the additional deleterious alleles that they generate, to a degree that will depend on how much they increase the mutation rate in heterozygotes and homozygotes. To describe their dynamics, we develop a population genetic model of mutation rate modifiers with arbitrary dominance coefficients, in which fitness effects stem from additional germline mutations. We then use it to interpret findings for the seven human mutators identified to date. For six of the seven known mutators, the observed frequencies are well fit by the model and thus consistent with purifying selection arising solely due to their effects on germline mutation rates, although also consistent with a wide range of parameters; in two, the observed frequencies are readily explained by purely recessive fitness effects. The exception is a variant in

Identifiers

PMID42779615
PMCPMC13596196

What OpenQuestion holds

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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.