Evidence map›Paper›PMID 40053834›Full record

ArticleG3 (Bethesda, Md.)2025

Recombinant inbred line panels inform the genetic architecture and interactions of adaptive traits in Drosophila melanogaster.

Tiago da Silva Ribeiro, Matthew J Lollar, Quentin D Sprengelmeyer, Yuheng Huang, Derek M Benson, Megan S Orr, Zachary C Johnson, Russell B Corbett-Detig, John E Pool

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 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

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

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Tiago da Silva RibeiroLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Matthew J LollarLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Quentin D SprengelmeyerLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Yuheng HuangLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0002-1586-953X
Derek M BensonLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Megan S OrrLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Zachary C JohnsonLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.
Russell B Corbett-DetigGenomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA.
John E PoolLaboratory of Genetics, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0003-2968-9545

Funding

The Architectures and Underpinnings of Adaptive Evolution and Reproductive IsolationR35GM136306 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI POOL, JOHN E · 2020 to 2025
$3.5M
Unraveling the Molecular and Population Genetic Complexity of Adaptive Trait EvolutionR01GM127480 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI POOL, JOHN E, REBEIZ, MARK J · 2019 to 2022
$1.3M
NIGMS NIH HHS R01 GM127480NIGMS NIH HHS R35 GM136306NIH HHS R01 GM127480
6 · The paper itself

Abstract

The distribution of allelic effects on traits, along with their gene-by-gene and gene-by-environment interactions, contributes to the phenotypes available for selection and the trajectories of adaptive variants. Nonetheless, uncertainty persists regarding the effect sizes underlying adaptations and the importance of genetic interactions. Herein, we aimed to investigate the genetic architecture and the epistatic and environmental interactions involving loci that contribute to multiple adaptive traits using 2 new panels of Drosophila melanogaster recombinant inbred lines (RILs). To better fit our data, we re-implemented functions from R/qtl using additive genetic models. We found 14 quantitative trait loci (QTLs) underlying melanism, wing size, song pattern, and ethanol resistance. By combining our mapping results with population genetic statistics, we identified potential new genes related to these traits. None of the detected QTLs showed clear evidence of epistasis, and our power analysis indicated that we should have seen at least 1 significant interaction if sign epistasis or strong positive epistasis played a pervasive role in trait evolution. In contrast, we did find roles for gene-by-environment interactions involving pigmentation traits. Overall, our data suggest that the genetic architecture of adaptive traits often involves alleles of detectable effect, that strong epistasis does not always play a role in adaptation, and that environmental interactions can modulate the effect size of adaptive alleles.

Indexed as

Adaptation, PhysiologicalDrosophila melanogasterInbreedingQuantitative Trait, HeritableRecombination, GeneticAnimalsChromosome MappingEpistasis, GeneticGene-Environment InteractionMaleModels, GeneticPhenotypePigmentationQuantitative Trait LociadaptationDrosophila melanogasterepistasisFlyBasequantitative geneticsquantitative trait loci (QTLs)

Identifiers

PMID40053834
PMCPMC12060232

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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.