Accuracy of genomic prediction for merino wool traits using high-density marker genotypes — ASN Events
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  2. Concurrent 16 - Genomic prediction in practice II
  3. Accuracy of genomic prediction for merino wool traits using high-density marker genotypes

Accuracy of genomic prediction for merino wool traits using high-density marker genotypes (#96)

Nasir Moghaddar 1 , Andrew Swan 2 , Julius Van der werf 1
  1. University of New England, Armidale, NSW, Australia
  2. Animal Genetics & Breeding Unit (AGBU), University of New England, Armidale, NSE, Australia

SUMMARY

               High-density marker genotypes could increase the accuracy of genomic prediction by providing stronger linkage disequilibrium (LD) between markers and quantitative trait loci, especially in populations with a high genetic diversity. The aim of this study was to compare the accuracy of genomic prediction for Merino yearling and adult wool traits based on imputed high-density (600k) single nucleotide polymorphisms (SNPs) marker genotypes to prediction based on moderate-density (50k) marker genotypes. Genomic best linear unbiased prediction (GBLUP) and a Bayesian approach (Bayes-R) were used as prediction methods. Results showed a relative increase in accuracy between 2 to 15% when using high-density marker set. The results of Bayes-R were on average similar to GBLUP. Increase in genomic prediction accuracy was higher for lowly heritable traits. Considerably higher (up to 25% relative increase) in prediction accuracy was observed for animals with lower genetic relationship to reference population.

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