Impact of Genomic Information on Variance Components Estimation in Small Populations with Incomplete Pedigree Information

Genomic information improves genetic breeding programs of dairy cattle. Many factors could influence the benefits that this technology provides. Genomic data could enhance the estimation of variance components, especially when pedigree information is incomplete in the studied population. The aim of this study was to measure the impact of including genomic information on the estimation of variance components for milk yield of first and second lactations. The analysis included 2,011 genotypes (previously imputed to 45,195 markers), phenotypes of genotyped animals and of their contemporaries (22,201 and 16,926 adjusted to 305 days mature-equivalent milk yield records for first and second lactations respectively) and available pedigree information of animals with phenotypic data (42,154 individuals). Pedigree completeness of the studied population was 76%. An animal model was implemented with herd-year-season, sire-herd interaction, animal and residual effects. The BLUPF90 (AIREMLF90) software was used to estimate variance components. When no genomic information was included in the analysis, heritabilities (h²) of milk yield for first and second lactations were 0.19 and 0.26 respectively and when genotypes were included, h² for first lactation increased slightly (h² = 0.20 ) while it decreased for second lactation (h² = 0.19). Results of this study indicate that the addition of genomic information to the evaluation of populations with incomplete pedigree information will translate into a decrease of the expected genetic improvement due to selection probably because of corrected additive relationships among animals.