ArticleCell genomics2026
Discovery and characterization of gene-by-environment and epistatic genetic effects in a vertebrate model.
Article in Cell genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenotypic variation arises from interactions between genetic and environmental factors, but disentangling these effects for complex traits remains challenging in observational cohorts like human biobanks. Model organisms with controlled genetic and environmental variation complement human studies in analyzing higher-order effects such as gene-by-environment (G×E) interactions, dominance, and epistasis. We utilized 76 medaka strains from the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel to compare heart rate plasticity across temperatures. An F2 segregation analysis identified 16 quantitative trait loci (QTLs), many exhibiting dominance, G×E, G×G, and G×G×E interactions. We experimentally validated four candidate genes, revealing temperature-sensitive heart rate effects. Finally, we simulated how genome-wide association study (GWAS) discovery power depends on statistical model choice. Our results suggest that the limited detection of non-additive effects in human GWASs stems from current study designs and sample sizes. This work demonstrates the value of controlled model organism studies for dissecting complex trait genetics and informing association study design.
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Registered trials
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