Abstract
BACKGROUND/OBJECTIVES: Genomic selection (GS) has improved accuracy compared to traditional methods. However, accuracy tends to plateau beyond a certain marker density. Prioritizing influential SNPs could further enhance the accuracy of GS. The fixation index (F(ST)) allows for the identification of SNPs under selection pressure. Although the F(ST) method was shown to be able to prioritize SNPs across the whole genome and to increase accuracy, its performance could be further improved by focusing on the prioritization process within QTL regions. METHODS: A trait with heritability of 0.1 and 0.4 was generated under different simulation scenarios (number of QTL, size of SNP windows around QTL, and number of selected SNPs within a QTL region). In total, six simulation scenarios were analyzed. Each scenario was replicated five times. The population comprised 30K animals from the last 2 generations (G9-G10) of a 10-generation (G1-G10) selection process. All animals in G9-10 were genotyped with a 600K SNP panel. F(ST) scores were calculated for all 600K SNPs. Two prioritization scenarios were used: (1) selecting the top 1% SNPs with the highest F(ST) scores, and (2) selecting a predetermined number of SNPs within each QTL window. GS accuracy was evaluated using the correlation between true and estimated breeding values for 5000 randomly selected animals from G10. RESULTS: Prioritizing SNPs using F(ST) scores within QTL window regions increased accuracy by 5 to 18%, with the 50-SNP windows showing the best performance. CONCLUSIONS: The increase in GS accuracy warrants the testing of the algorithm when the number and position of QTL are unknown.