Genomic prediction using QTL derived from whole genome sequence data

Abstract Text: This study investigated the gain in accuracy of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k SNP data. Analyses were performed for Nordic Holstein and Danish Jersey animals, using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model, results showed increases in accuracy of up to two percentage points for production traits in both Holstein and Jersey animals by including the extra variants in the analysis, and an extra 1.5 percentage points for fertility in Jersey animals. When using a Bayesian model accuracies were generally higher, but only small increases in accuracy of up to 0.6 percentage points were observed for the Holstein animals when including the extra markers, while both increases and decreases were observed for Jersey. 

Keywords: Custom chip, genomic prediction, QTL