Fine-tuning genomic and pedigree inbreeding rates in equine population with a deep and reliable stud book: the case of the Pura Raza Española horse

BACKGROUND: Estimating inbreeding, which is omnipresent and inevitable in livestock populations, is a primary goal for management and animal breeding especially for those interested in mitigating the negative consequences of inbreeding. Inbreeding coefficients have been historically estimated by using pedigree information; however, over the last decade, genome-base inbreeding coefficients have come to the forefront in this field. The Pura Raza Española (PRE) horse is an autochthonous Spanish horse breed which has been recognised since 1912. The total PRE population (344,718 horses) was used to estimate Classical (F), Ballou’s ancestral, Kalinowski’s ancestral, Kalinowski’s new and the ancestral history coefficient values. In addition, genotypic data from a selected population of 805 PRE individuals was used to determine the individual inbreeding coefficient using SNP-by-SNP-based techniques (methods of moments -F(HOM)-, the diagonal elements of the genomic -F(G)-, and hybrid matrixes -F(H)-) and ROH measures (F(RZ)). The analyse of both pedigree and genomic based inbreeding coefficients in a large and robust population such as the PRE horse, with proven parenteral information for the last 40 years and a high degree of completeness (over 90% for the last 70 years) will allow us to understand PRE genetic variability better and the correlations between the estimations will give the data greater reliability. RESULTS: The mean values of the pedigree-based inbreeding coefficients ranged from 0.01 (F for the last 3 generations -F3-) to 0.44 (ancestral history coefficient) and the mean values of genomic-based inbreeding coefficients varied from 0.05 (F(RZ) for three generations, F(H) and F(HOM)) to 0.11 (F(RZ) for nine generations). Significant correlations were also found between pedigree and genomic inbreeding values, which ranged between 0.58 (F3 with F(HOM)) and 0.79 (F with F(RZ)). In addition, the correlations between F(RZ) estimated for the last 20 generations and the pedigree-based inbreeding highlight the fact that fewer generations of genomic data are required when comparing total inbreeding values, and the opposite when ancient values are calculated. CONCLUSIONS: Ultimately, our results show that it is still useful to work with a deep and reliable pedigree in pedigree-based genetic studies with very large effective population sizes. Obtaining a satisfactory parameter will always be desirable, but the approximation obtained with a robust pedigree will allow us to work more efficiently and economically than with massive genotyping.