Evidence map›Paper›PMID 40596731›Full record

ArticleNature ecology & evolution2025

Deep learning reveals the complex genetic architecture of male guppy colouration.

Wouter van der Bijl, Jacelyn J Shu, Versara S Goberdhan, Linley M Sherin, Changfu Jia, Maria Cortazar-Chinarro, Alberto Corral-Lopez, Judith E Mank

Abstract read
PubMed Publisher
In one paragraph

Article in Nature ecology & evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Beyond the Classics: The Synergy of AI and Genomics Reveals an Expanded Repertoire of Pigmentation Genes.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2026
    Review
  5. Immediate Background Color Choice in Male and FemaleAnimals : an open access journal from MDPI · 2026
    Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Article
  12. 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

8 authors.

Wouter van der BijlDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada. wouter@zoology.ubc.ca.ORCID http://orcid.org/0000-0002-7366-1868
Jacelyn J ShuDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Versara S GoberdhanDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Linley M SherinDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.ORCID http://orcid.org/0000-0003-0780-221X
Changfu JiaDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Maria Cortazar-ChinarroDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.
Alberto Corral-LopezDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.ORCID http://orcid.org/0000-0001-7784-0209
Judith E MankDepartment of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 680951Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada) Canada 150 ChairGouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada) RGPIN-2020-03867
6 · The paper itself

Abstract

The extraordinary variation in male guppy (Poecilia reticulata) colouration is a powerful model for studying the interplay of natural and sexual selection. However, the complexity of this variation has hampered the high-resolution characterization and determination of the genetic architecture underlying male guppy colour and clouded our understanding of how this exceptional level of diversity is maintained. Here we identify the heritability and genetic basis of male colour variation using convolutional neural networks for high-resolution phenotyping coupled with selection experiments, controlled pedigrees and whole-genome resequencing for a genome-wide association study of colour traits. Our phenotypic and genomic results converge to show that colour patterning in guppies is a combination of many heritable features, each with a largely independent genetic architecture spanning the entire genome. Autosomally inherited ornaments are polygenic, with significant contributions from loci involved in neural crest cell migration. Unusually, the results of our genome-wide association study suggest that gene duplicates from the autosomes to the Y chromosome are responsible for much of the sex-linked variation in colour in guppies, providing a potential mechanism for the maintenance of variation of this classic model trait.

Indexed as

Deep LearningPigmentationPoeciliaAnimalsGenome-Wide Association StudyMalePhenotype

Identifiers

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.