Inference of genotype probabilities and derived statistics for PrP locus in the Jezersko–Solcava sheep

Abstract

The aim of this work was to infer PrP genotype probabilities and derived statistics in sheep to provide additional information for selection against susceptibility to classical scrapie. The method was demonstrated with data from Jezersko–Solcava sheep breed. Pedigree data consisted of 10429 animals of which 3669 animals had known PrP genotype and 2673 were alive and not genotyped. Five PrP alleles were present with the following frequencies: ARR 0.174, AHQ 0.074, ARH 0.083, ARQ 0.632, and VRQ 0.037. Iterative allelic peeling with incomplete penetrance model as implemented in the GenoProb program was used to infer genotype probabilities. There were only some additional identifications of PrP genotype and NSP (national scrapie plan) type with high probability. The main reasons for a low number of additional identifications can be attributed to the large number of alleles with moderate frequencies, incomplete penetrance model, uniform prior, and inherent pedigree and genotype data structure. In order to overcome the limits of additional genotype identifications novel statistics were derived (maximal NSP type, average NSP value and its variance and reliability) to facilitate practical implementation of selection for scrapie resistance based on NSP types. Maximal NSP type can be used to infer maximal potential scrapie susceptibility of individual animals as well as for the entire flocks. The average NSP value encompasses all information contained in PrP genotype probabilities and is the most useful statistic for the selection on NSP type and therefore PrP genotype. These novel statistics can be used as a criterion for the selection against scrapie susceptibility for the whole population taking into the account possible errors in genotype and/or pedigree data.