Pedigree-tracking improved population monitoring of recessive disease-causing alleles in pedigreed canine populations
- 1The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh
Abstract
Background Most monogenic inherited diseases in dogs are recessive, so their successful control depends on genetic testing to identify carriers of the disease-causing allele. However, currently used methods for disease allele monitoring in canine populations typically only consider part of the entire pedigree, since not all dogs have a known genotype through genetic test or "hereditary status" (a determinable genotype assigned to offspring based on known parental genotypes). Methods This study uses probabilistic inference with unknown parent groups (UPGs) in five Royal Kennel Club (RKC)-registered pedigrees to estimate genotype probabilities for all individuals using available genetic test results for two monogenic recessive diseases: primary lens luxation (PLL) and progressive retinal atrophy rod-cone degeneration 4 (PRA-rcd4). From these estimates, the population trends in disease-causing allele frequencies were estimated, and the inference quality was assessed through leave-one-out cross-validation and simulation. Results For dogs born after the introduction of the genetic test, the estimated disease-causing allele frequencies differed between methods. For instance, dogs born in 2020 reported up to 0.092 higher disease-causing allele frequencies with estimated genotype probabilities than those based on genetic tests and hereditary status alone. Inference performance varied across breeds, dependent on population allele frequency, with Pearson correlations between true (per genetic test result) and estimated allele dosages ranging from 0.47 to 0.67. The gene drop simulations indicated a tendency to underestimate disease-causing allele frequencies in retrospective estimates, particularly for dogs born before 1990. Impact Overall, by leveraging all available pedigree and genetic test data through probabilistic pedigree-based inference, disease-causing allele frequencies were monitored more comprehensively within the pedigreed population rather than relying on genetic test results or hereditary status alone. Such monitoring can inform responsible breeding decisions, helping to conserve genetic diversity whilst supporting improvements in future canine health and welfare.
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BibTeX
@misc{craddock2026pedigreetracking,
title = {{Pedigree-tracking improved population monitoring of recessive disease-causing alleles in pedigreed canine populations}},
author = {R. F. Craddock and M. Janes Fistric and C. Mellersh and J. J. Ilska and P. Wiener and S. Smith and G. Gorjanc},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.27.761507},
url = {https://www.biorxiv.org/content/10.64898/2026.10.27.761507v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Pedigree-tracking improved population monitoring of recessive disease-causing alleles in pedigreed canine populations
AU - R. F. Craddock
AU - M. Janes Fistric
AU - C. Mellersh
AU - J. J. Ilska
AU - P. Wiener
AU - S. Smith
AU - G. Gorjanc
PY - 2026
DA - 2026/10/27
PB - bioRxiv
DO - 10.64898/2026.10.27.761507
UR - https://www.biorxiv.org/content/10.64898/2026.10.27.761507v1
AB - Background Most monogenic inherited diseases in dogs are recessive, so their successful control depends on genetic testing to identify carriers of the disease-causing allele. However, currently used methods for disease allele monitoring in canine populations typically only consider part of the entire pedigree, since not all dogs have a known genotype through genetic test or "hereditary status" (a determinable genotype assigned to offspring based on known parental genotypes). Methods This study uses probabilistic inference with unknown parent groups (UPGs) in five Royal Kennel Club (RKC)-registered pedigrees to estimate genotype probabilities for all individuals using available genetic test results for two monogenic recessive diseases: primary lens luxation (PLL) and progressive retinal atrophy rod-cone degeneration 4 (PRA-rcd4). From these estimates, the population trends in disease-causing allele frequencies were estimated, and the inference quality was assessed through leave-one-out cross-validation and simulation. Results For dogs born after the introduction of the genetic test, the estimated disease-causing allele frequencies differed between methods. For instance, dogs born in 2020 reported up to 0.092 higher disease-causing allele frequencies with estimated genotype probabilities than those based on genetic tests and hereditary status alone. Inference performance varied across breeds, dependent on population allele frequency, with Pearson correlations between true (per genetic test result) and estimated allele dosages ranging from 0.47 to 0.67. The gene drop simulations indicated a tendency to underestimate disease-causing allele frequencies in retrospective estimates, particularly for dogs born before 1990. Impact Overall, by leveraging all available pedigree and genetic test data through probabilistic pedigree-based inference, disease-causing allele frequencies were monitored more comprehensively within the pedigreed population rather than relying on genetic test results or hereditary status alone. Such monitoring can inform responsible breeding decisions, helping to conserve genetic diversity whilst supporting improvements in future canine health and welfare.
ER -