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Inference of admixture in dogs from whole genome sequences
Gregory Kislik1, Garrett Moore2, Liudmilla Rubbi1
1Molecular Cell and Developmental Biology, University of California, Los Angeles (UCLA), CA, Los Angeles, USA.
Gigabyte (Hong Kong, China)
|March 30, 2026
Summary
We developed a new method to estimate global admixture in dogs using whole genome data. This approach accurately infers breed composition, even with limited sequencing, providing insights into canine genetic diversity.
Area of Science:
- Canine genetics
- Population genetics
- Genomics
Background:
- Domestic dogs exhibit diverse morphologies and behaviors, with extensive historical and ongoing admixture shaping their genomes.
- Widespread genetic mixing in dogs results from natural migration and selective breeding practices.
- Limited analysis of global admixture in canines compared to human populations, despite numerous ancestral groups.
Purpose of the Study:
- To present a novel procedure for estimating global admixture in dogs using whole genome sequence data.
- To develop and validate a method for accurate breed composition inference in admixed canines.
- To characterize genetic similarities among dog breeds and understand admixture patterns.
Main Methods:
- Utilized whole genome sequence data from a reference population of 65 dog breeds (349 individuals).
- Developed a method (SCOPE) to identify breed-informative single nucleotide polymorphisms (SNPs).
- Applied SCOPE to infer breed composition in simulated and real admixed canine samples, including those with low sequencing depths.
Main Results:
- SCOPE accurately infers breed composition in admixed dog samples, even at low sequencing depths.
- The method successfully characterized genetic similarities between reference dog breeds, aligning with previously reported relationships.
- Demonstrated the ability to identify the strength of breed genetic signatures and establish error bounds for admixture estimates.
Conclusions:
- The developed approach accurately estimates global admixture in dogs from whole genome data.
- This method provides reliable breed composition inference for canines with complex ancestral origins.
- The findings enhance our understanding of canine domestication, breed formation, and the genetic basis of traits and diseases.
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