Forensic use of the genomic relationship matrix to validate and discover livestock pedigrees

Correct pedigree is essential to produce accurate genetic evaluations of livestock populations. Pedigree validation has traditionally been undertaken using microsatellites and more recently, based on checks on opposing homozygotes using single nucleotide polymorphisms (SNPs). In this study, the genomic relationship matrix was examined to see whether it was a useful tool to forensically validate pedigree and discover unknown pedigree. Using 5,993 genotyped Limousin animals which were imputed to a core set of 38,907 SNPs, the genomic relationships between animals were assessed to validate the reported pedigree. Using already pedigree-verified animals, the genomic relationships between animals of different relationships were shown to be on average 0.58, 0.59, 0.32, 0.32, 0.19, and 0.14 between animals and their parents, full siblings, half siblings, grandparents, great grandparents, and great great grandparents, respectively. Threshold values were defined based on the minimum genomic relationship reported between already pedigree-verified animals; 0.46, 0.41, 0.17, 0.17, 0.07, and 0.05, respectively for animals and their parents, full siblings, half siblings, grandparents, great grandparents, and great great grandparents. Using the wider population and the above genomic relationship threshold values, potential pedigree conflicts were identified within each relationship type. Pedigree error rates of between 0.9% (animal and great great grandparent) and 4.0% (full siblings) were identified. A forensic genomic pedigree validation and discovery system was developed to enable pedigree to be verified for individual genotyped animals. This system verifies not just the parents, but also a wide number of other genotyped relatives and can therefore identify more potential errors in the pedigree than current conventional methods. A novel aspect to this algorithm is that it can also be used to discover closely related animals on the basis of their genomic relationships although they are not recorded as such in the pedigree. This functionality enables missing pedigree information to be discovered and corrected in the pedigree of livestock populations. The methods in this paper demonstrate that the genomic relationship matrix can be a useful tool in the validation and discovery of pedigree in livestock populations. However, the method does rely on being able to define threshold values appropriate to the specific livestock population, which will require sufficient number of animals to be genotyped and pedigree validated before it can be used.