Estimation of inbreeding using pedigree, 50k SNP chip genotypes and full sequence data in three cattle breeds

<p>Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. Various estimators based on different sources, e.g., pedigree or genomic data, have been used to estimate inbreeding coefficients in cattle populations. However, the comparative advantage of using full sequence data to assess inbreeding is unknown. We used pedigree and genomic data at different densities from 50k to full sequence variants to compare how different methods performed for the estimation of inbreeding levels in three different cattle breeds. Results: Five different estimates for inbreeding were calculated and compared in this study: pedigree based inbreeding coefficient (F_PED); run of homozygosity (ROH)-based inbreeding coefficients (F_ROH); genomic relationship matrix (GRM)-based inbreeding coefficients (F_GRM); inbreeding coefficients based on excess of homozygosity (F_HOM) and correlation of uniting gametes (F_UNI). Estimates using ROH provided the direct estimated levels of autozygosity in the current populations and are free effects of allele frequencies and incomplete pedigrees which may increase in inaccuracy in estimation of inbreeding. The highest correlations were observed between F_ROH estimated from the full sequence variants and the F_ROH estimated from 50k SNP (single nucleotide polymorphism) genotypes. The estimator based on the correlation between uniting gametes (F_UNI) using full genome sequences was also strongly correlated with F_ROH detected from sequence data. Conclusions: Estimates based on ROH directly reflected levels of homozygosity and were not influenced by allele frequencies, unlike the three other estimates evaluated (F_GRM, F_HOM and F_UNI), which depended on estimated allele frequencies. F_PED suffered from limited pedigree depth. Marker density affects ROH estimation. Detecting ROH based on 50k chip data was observed to give estimates similar to ROH from sequence data. In the absence of full sequence data ROH based on 50k can be used to access homozygosity levels in individuals. However, genotypes denser than 50k are required to accurately detect short ROH that are most likely identical by descent (IBD).