Abstract
Trait heritability is necessary for evolution by both natural and artificial selection, yet we know little about the heritability of cognitive traits. Domestic dogs are a valuable study system for questions regarding the evolution of phenotypic diversity due to their extraordinary intraspecific variation. While previous studies have investigated morphological and behavioral variation across dog breeds, few studies have systematically assessed breed differences in cognition. We integrated data from Dognition.com—a citizen science project on dog cognition—with breed-averaged genetic data from published sources to estimate the among-breed heritability of cognitive traits using mixed models. The resulting dataset included 11 cognitive measures for 1508 adult dogs across 36 breeds. A factor analysis yielded four factors interpreted as reflecting inhibitory control, communication, memory, and physical reasoning. Narrow-sense among-breed heritability estimates—reflecting the proportion of cognitive variance attributable to additive genetic variation—revealed that scores on the inhibitory control and communication factors were highly heritable (inhibitory control: h2 = 0.70; communication: h2 = 0.39), while memory and physical reasoning were less heritable (memory: h2 = 0.17; physical reasoning: h2 = 0.21). Although the heritability of inhibitory control is partially explained by body weight, controlling for breed-average weight still yields a high heritability estimate (h2 = 0.50), while other factors are minimally affected. Our results indicate that cognitive phenotypes in dogs covary with breed relatedness and suggest that cognitive traits have strong potential to undergo selection. The highest heritabilities were observed for inhibitory control and communication, both of which are hypothesized to have been altered by domestication.
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Acknowledgements
We thank David Ivy, Eliot Cohen, Kip Frey, and everyone else who helped create Dognition.com, as well as the members of the advisory board: Josep Call, Juliane Kaminski, Ádám Miklósi, Laurie R. Santos, and Richard Wrangham. We thank Daniel J. Horschler for discussions of the Dognition data and sharing already-tabulated breed-average body weight data, as well as Stacey R. Tecot, Ivy L. Pike, and two anonymous reviewers for comments on previous versions of this manuscript. Lastly, we thank all the dogs and people who participated in Dognition and made this work possible. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. (DGE-1746060). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Funding
G.E.G. was funded by the University of Arizona’s University Fellows Program and the NSF Graduate Research Fellowship Program (DGE-1746060). B.H. is supported in part by the National Institute of Health (Grant 1R01HD097732-01).
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The data was collected by citizen scientists through Dognition, with tasks designed by BH. The analysis was primarily designed and conducted by GEG and ELM, with BH and NS-M consulting. The paper was written primarily by GEG with significant contributions and revisions from ELM, BH, and NS-M All authors gave their final approval for publication and agree to be held accountable for the work performed therein.
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BH is a founder of Dognition.com and a member of its Scientific Advisory Board. The authors declare no other competing interests.
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All animals included in this study were pet dogs tested by citizen scientists in their own homes. The use of third-party data from Dognition.com was approved by Duke University IACUC protocol A138-11-06 and data were collected in accordance with relevant guidelines and regulations.
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Genetic data used in these analyses are available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.266k4 (Hayward et al. 2016b) and GEO accession nos. GSE90441, GSE83160, GSE70454 and GSE96736. A subset of the Dognition data and the code for our linear mixed models are available at https://github.com/GGnanadesikan/dognition_heritability/. The remaining Dognition data used in these analyses are available from Brian Hare at b.hare@duke.edu.
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Gnanadesikan, G.E., Hare, B., Snyder-Mackler, N. et al. Estimating the heritability of cognitive traits across dog breeds reveals highly heritable inhibitory control and communication factors. Anim Cogn 23, 953–964 (2020). https://doi.org/10.1007/s10071-020-01400-4
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DOI: https://doi.org/10.1007/s10071-020-01400-4