Author ORCID Identifier

Halie M. Rando: 0000-0001-7688-1770

Document Type

Article

Publication Date

5-1-2024

Publication Title

Journal of the American Veterinary Medical Association

Abstract

OBJECTIVE To compare pedigree documentation and genetic test results to evaluate whether user-provided photographs influence the breed ancestry predictions of direct-to-consumer (DTC) genetic tests for dogs.

ANIMALS 12 registered purebred pet dogs representing 12 different breeds. METHODS Each dog owner submitted 6 buccal swabs, 1 to each of 6 DTC genetic testing companies. Experimenters registered each sample per manufacturer instructions. For half of the dogs, the registration included a photograph of the DNA donor. For the other half of the dogs, photographs were swapped between dogs. DNA analysis and breed ancestry prediction were conducted by each company. The effect of condition (ie, matching vs shuffled photograph) was evaluated for each company’s breed predictions. As a positive control, a convolutional neural network was also used to predict breed based solely on the photograph. RESULTS Results from 5 of the 6 tests always included the dog’s registered breed. One test and the convolutional neural network were unlikely to identify the registered breed and frequently returned results that were more similar to the photograph than the DNA. Additionally, differences in the predictions made across all tests underscored the challenge of identifying breed ancestry, even in purebred dogs.

CLINICAL RELEVANCE Veterinarians are likely to encounter patients who have conducted DTC genetic testing and may be asked to explain the results of genetic tests they did not order. This systematic comparison of commercially available tests provides context for interpreting results from consumer-grade DTC genetic testing kits.

Keywords

breed ancestry, canine genetics, deep learning, direct-to-consumer, genetic testing

Volume

262

Issue

5

DOI

10.2460/javma.23.07.0372

ISSN

00031488

Comments

Archived as published.

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