Evidence map›Paper›PMID 41993497›Full record

ArticlebioRxiv : the preprint server for biology2026

Laboratory yeast crosses reveal limited epistasis in the genetic basis of complex traits.

Misha Gupta, Caroline M Holmes, Jenya Belousova, Shreyas Gopalakrishnan, Artur Rego-Costa, Michael M Desai

Abstract readPreprint
PubMed Full text at PMC Publisher
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

6 authors.

Misha GuptaDepartment of Organismic and Evolutionary Biology, Harvard University.ORCID 0000-0003-3741-5659
Caroline M HolmesDepartment of Organismic and Evolutionary Biology, Harvard University.
Jenya BelousovaDepartment of Organismic and Evolutionary Biology, Harvard University.
Shreyas GopalakrishnanDepartment of Molecular and Cell Biology, Harvard University.
Artur Rego-CostaDepartment of Organismic and Evolutionary Biology, Harvard University.
Michael M DesaiDepartment of Organismic and Evolutionary Biology, Harvard University.

Funding

Microbial Adaptation and the Statistics of Epistasis and PleiotropyR01GM104239 · NIGMS · HARVARD UNIVERSITY · PI DESAI, MICHAEL M · 2013 to 2025
$4.5M
NIGMS NIH HHS R01 GM104239
6 · The paper itself

Abstract

Mapping the genetic basis of complex traits is complicated by the presence of epistatic interactions between loci. While work in molecular genetics identifies numerous specific genetic interactions, statistical analyses of quantitative traits frequently conclude that additive (nonepistatic) models explain most heritable variation. However, these conclusions are typically limited by the narrow range of genetic relatedness(e.g. in F1 offspring of a biparental or circular cross). Here, we use a barcoded panel of

Identifiers

PMID41993497
PMCPMC13082033

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.