Estimating breed composition for pigs: A case study focused on Mangalitsa pigs and two methods

Breed associations and registries maintain breed purity by enforcing certain conformational characteristics defining the along with cataloging pedigree of every animal in registry. Furthermore, developing niche markets is often based on specialized products using heritage breeds that need to guarantee purity. Genomic technology progressively lower costs genotyping can be helpful when assessing estimating composition. In this research, genotypes from 648 pigs 11 were used develop marker panels estimate composition special emphasis Mangalitsa as a breed. Two sets created. The first set was Fst scores calculated individually for ~31,000 available markers across pig genome. Here, composed 10, 50, 100, 500 1000 highest generated. second randomly selected had same number Fst-derived panels. statistical methods, linear regression random forest then composition, 107 including 47 individuals known have background. appeared better at identifying compared regardless method However, more accurate non-Mangalitsa individuals. When results methods produced estimates than forest. both lacked accuracy crossbred It must also noted these focused different should if will focus prediction depend are references calculations. presented study allow us conclude that: 1) Random effective classifying into breeds, but not method. 2) Markers filtered while other breeds. 3) If Fst-filtered being greater needed.