Evidence map›Paper›PMID 39999028›Full record

ArticleGenetics2025

The divergence of mean phenotypes under persistent Gaussian selection.

Michael Lynch, Scott Menor

Abstract read
In one paragraph

Article in Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

3 citing papers in PubMed.

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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

2 authors.

Michael LynchBiodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA.
Scott MenorBiodesign Center for Mechanisms of Evolution, Arizona State University, Tempe, AZ 85287, USA.

Funding

Causes and Population-genetic Consequences of Molecular VariationR35GM122566 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI Michael R LYNCH · 2017 to 2026
$7.7M
Moore and Simons Foundations 735927Multidisciplinary University Research Initiative W911NF-09-1-0444National Science Foundation DBI-2119963NIGMS NIH HHS R35 GM122566NIH HHS R35-GM122566US Army Research Office
6 · The paper itself

Abstract

Although multigenic traits are often assumed to be under some form of stabilizing selection, numerous aspects of the population-genetic environment can cause mean phenotypes to deviate from presumed optima, often in ways that effectively transform the fitness landscape to one of directional selection. Focusing on an asexual population, we consider the ways in which such deviations scale with the relative power of selection and genetic drift, the number of linked genomic sites, the magnitude of mutation bias, and the location of optima with respect to possible genotypic space. Even in the absence of mutation bias, mutation will influence evolved mean phenotypes unless the optimum happens to coincide exactly with the mean expected under neutrality. In the case of directional mutation bias and large numbers of selected sites, effective population sizes (Ne) can be dramatically reduced by selective interference effects, leading to further mismatches between phenotypic means and optima. Situations in which the optimum is outside or near the limits of possible genotypic space (e.g. a half-Gaussian fitness function) can lead to particularly pronounced gradients of phenotypic means with respect to Ne, but such gradients can also occur when optima are well within the bounds of attainable phenotypes. These results help clarify the degree to which mean phenotypes can vary among populations experiencing identical mutation and selection pressures but differing in Ne, and yield insight into how the expected scaling relationships depend on the underlying features of the genetic system.

Indexed as

Models, GeneticPhenotypeSelection, GeneticGenetic DriftGenetic FitnessGenetics, PopulationGenotypeMutationNormal DistributionPopulation Densityevolutionary divergenceGaussian selectionmutation biasphenotypic divergencephenotypic scalingrandom genetic driftselective interferencestabilizing selection

Identifiers

PMID39999028
PMCPMC12005259

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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.