Evidence map›Paper›PMID 40891677›Full record

ArticleeLife2025

The Product neutrality function defining genetic interactions emerges from mechanistic models of cell growth.

Lucas Fuentes Valenzuela, Paul Francois, Jan M Skotheim

Abstract read
In one paragraph

Article in eLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Lucas Fuentes ValenzuelaDepartment of Biology, Stanford University, Stanford, United States.ORCID https://orcid.org/0009-0002-7403-3537
Paul FrancoisDepartment of Biochemistry and Molecular Medicine, University of Montreal, Montreal, Canada.ORCID https://orcid.org/0000-0002-2223-839X
Jan M SkotheimDepartment of Biology, Stanford University, Stanford, United States.ORCID https://orcid.org/0000-0001-8420-6820

Funding

Determining how cell growth triggers cell divisionR35GM134858 · NIGMS · STANFORD UNIVERSITY · PI Jan M Skotheim · 2020 to 2026
$4.1M
NIGMS NIH HHS R35 GM134858NIH HHS GM134858
6 · The paper itself

Abstract

Genetic analyses, which examine the phenotypic effects of mutations both individually and in combination, have been fundamental to our understanding of cellular functions. Such analyses rely on a neutrality function that predicts the expected phenotype for double mutants based on the phenotypes of the two individual non-interacting mutations. In this study, we examine fitness, the most fundamental cellular phenotype, through an analysis of the extensive colony growth rate data available for budding yeast. Our results confirm that the Product neutrality function describes the colony growth rate, or fitness, of a double mutant as the product of the fitnesses of the individual single mutants. This Product neutrality function performs better than Additive or Minimum neutrality functions, supporting its continued use in genetic interaction studies. Furthermore, we explore the mechanistic origins of this neutrality function by analyzing two theoretical models of cell growth. We perform a computational genetic analysis to show that in both models, the Product neutrality function naturally emerges due to the interdependence of cellular processes that maximize growth rates. Thus, our findings provide mechanistic insight into how the Product neutrality function arises and affirm its utility in predicting genetic interactions affecting cell growth and proliferation.

Indexed as

Cell ProliferationEpistasis, GeneticModels, GeneticSaccharomyces cerevisiaeSaccharomycetalesMutationPhenotypebudding yeastcell growthcomputational biologyepistasisgenetic interactionsquantitative geneticsS. cerevisiaesystems biology

Identifiers

PMID40891677
PMCPMC12404613

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.