Genomic inbreeding coefficients using imputed genotypes: Assessing different estimators in Holstein-Friesian dairy cows

The objective of this study was to estimate inbreeding coefficients in Holstein dairy cattle using imputed SNPs data. A data set of 95,540 Italian Holstein dairy cows from the routine genomic evaluations of the Italian National Association of Holstein, Brown, and Jersey Breeders were analyzed, with 84,445 imputed SNP. Ten widely used genomic inbreeding estimators were tested, including 4 PLINK v1.9 estimators (F, F_HAT1, F_HAT2, F_HAT3), 3 genomic relationship matrix (GRM)-based methods VanRaden's first method with observed allele frequencies (F_GRM) or with fixed frequencies at 0.5 (F_GRM05), VanRaden's third method, allelic frequency free and pedigree regressed (F_GRM2)], runs of homozygosity (ROH)-based estimators in a complete (F_ROH) and simplified version (F_ROH2), and proportion of homozygous SNP (F_PH). Pairwise comparisons among them were made, including the comparison with traditional pedigree-based inbreeding coefficients (F_PED). Our results showed variability among the genomic inbreeding estimators. Coefficients of F_GRM and F_HAT3 were >1, meaning that more variability has been lost than the variability that existed in the base population. Regarding the remaining ones, F_GRM05, F_ROH, F_ROH2, and F_PH provided coefficients within the 0,1] space and are considered comparable to F_PED. Not comparable to F_PED, yet with an interpretable value, can be considered the coefficients of F, F_HAT2, and F_GRM2. Estimators based on ROH had the highest correlation with pedigree-based coefficients (0.59–0.66), among all estimators tested. In this study, Spearman correlations were shown to possibly provide a clearer estimation of the strength of the relationship between estimators. We hypothesize that imputation might cause extreme genomic inbreeding values that deserves further investigation.