Genetic testing predicts appearance but not behavior in dogs
Abstract
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.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (8)
Kathryn A. Lord
Genomics and Computational Biology, University of Massachusetts Chan Medical School
Vista Sohrab
Genomics and Computational Biology, UMass Chan Medical School
Kasia Bryc
Medical and Population Genetics Program, Broad Institute of MIT and Harvard
Michelle E. White
Medical and Population Genetics Program, Broad Institute of MIT and Harvard
Brittney Kenney
Genomics and Computational Biology, UMass Chan Medical School
Kathleen Morrill Pirovich
Genomics and Computational Biology, UMass Chan Medical School
Frances L. Chen
Genomics and Computational Biology, UMass Chan Medical School
Elinor K. Karlsson
Genomics and Computational Biology, University of Massachusetts Chan Medical School