Genetic testing predicts appearance but not behavior in dogs

• 成果类型: Article
• 署名作者: Lord, Kathryn A.; Sohrab, Vista; Bryc, Kasia; White, Michelle E.; Kenney, Brittney; Pirovich, Kathleen Morrill; Chen, Frances L.; Karlsson, Elinor K.
• 署名单位: University of Massachusetts System; UMass Chan Medical School; University of Massachusetts Worcester; Harvard University; Massachusetts Institute of Technology (MIT); Broad Institute; University of Massachusetts System; UMass Chan Medical School; University of Massachusetts Worcester
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.2421752122
• 发表日期: 2025-12-02
• 页码: e2421752122
• 关键词: genomic prediction; Genetic testing; BEHAVIOR; dog; artificial selection; polygenic risk scores; coat color; DOMESTIC DOG; population-structure; MAJOR DETERMINANT; FGF4 RETROGENE; Mutation; selection; association; phenotypes

摘要

Genetic tests for behavioral and personality traits in dogs are now being marketed to pet owners, but their predictive accuracy has not been validated. To evaluate the reliability of such tests, we analyzed data from Darwin's Ark, a community science initiative that includes over 3,000 dogs with both genetic data and individual- level behavioral phenotypes. None of the candidate variants had significant associations or predictive power for behavioral traits as previously reported. However, we found strong associations with aesthetic traits that differentiate breeds, such as height, leg length, and ear shape. Our results suggest that earlier studies using breed- average phenotypes, rather than individually measured phenotypes, were confounded by population structure. Behavior in dogs is polygenic and complex, and thus cannot be accurately predicted using tests that consider only a few genetic variants. Furthermore, behavior in dogs is only moderately heritable, and environmental influences inherently limit the potential accuracy of genomic predictions. Developing meaningful, accurate genetic predictions for complex traits that can improve dog health and welfare will require very large cohorts of individually phenotyped dogs.