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Leonberger

Leonberger genetic profile from the CanVAS Atlas. 25 dogs in the Atlas, heterozygosity 0.31. Nearest relatives, trait loci frequencies, cohort distribution.

What the atlas says about Leonberger

In the atlas, the Leonberger clusters consistently as Leonberger (100% of the 25 dogs here). At the trait loci, SMOC2 runs lower than average (2% here vs 75%); STC2 runs lower than average (12% here vs 74%). Dogs here sit in a relatively sparse region of the atlas, fewer close neighbors than typical.

Only 25 dogs of this breed in the atlas, modestly sampled.

Closest genetic neighbors in the atlas: Rottweiler, Saint Bernard, Newfoundland, mixed breed, and Bernese Mountain Dog.

Median lifespan is 10.0 years, slightly shorter than expected for the breed size (59.25 kg).

Genetic dimensions · CanVAS atlas

What the genome says about Leonberger

Computed from the 14,478 research dogs in the Atlas. Methods: technical methodology.

Dogs in the Atlas
25Founders
13 from Hayward2016, 10 from Spatola, 2 from JenkinsWGS
Genetic diversity
0.31Moderate
Mean heterozygosity across the breed. Ranks 61st most genetically tight of 107 ranked breeds.
Cluster structure
Single tight cluster
Intra-breed RMS distance: 23.54
Nearest genetic relatives
  1. Rottweiler3.87
  2. Saint Bernard4.95
  3. Newfoundland6.36
  4. Mix7.43
  5. Bernese Mountain Dog7.54
Top-10 PC corrected Euclidean. Lower = closer.
Trait genetics
Allele frequencies at named morphology loci

Frequency of the alternate allele in this breed at each locus's representative SNP. Methods + caveats in technical methodology.

Body size
IGF143%
HMGA268%
SMAD262%
LCORL78%
STC213%
ADAMTS1780%
Leg length
FGF4·CFA1888%
FGF4·CFA1278%
Coat
RSPO271%
FGF5100%
KRT7194%
MC1R100%
Ear set
MSRB3100%
Skull shape
BMP397%
SMOC22%
Add your Leonberger to the Atlas

You can add your Leonberger right now at /add/ as a Charted star. Or, if you'd rather wait for DNA uploads, leave your email and we'll let you know the moment those open.

Last updated
Sources: CanVAS (Brundage 2026) · CanVAS dimensions data