Genomic predictions for meat colour traits in New Zealand sheep — ASN Events
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Genomic predictions for meat colour traits in New Zealand sheep (#38)

Luiz F Brito 1 , Stephen P Miller 2 , Michael A Lee 3 , Duc Lu 2 , Ken G Dodds 2 , Natalie K Pickering 4 , Wendy E Bain 2 , Flavio S Schenkel 5 , John C McEwan 2 , Shannon M Clarke 2
  1. University of Guelph/AgResearch, Mosgiel, OTAGO, New Zealand
  2. Animal Genomics, AgResearch, Mosgiel, Otago, Dunedin
  3. Mathematics and Statistics, University of Otago, Dunedin, Otago, New Zealand
  4. Genetics, Focus Genetics, Napier, New Zealand
  5. Animal Science, University of Guelph, Guelph, Ontario, Canada

The aim of this study was to evaluate the accuracy of genomic prediction for lamb meat colour traits in New Zealand sheep. A total number of 7,602 animals born between 2010 and 2013 were genotyped with the High-Density Ovine BeadChip containing 606,006 single nucleotide polymorphisms. The traits included in this study were: loin redness (A24), yellowness (B24) and lightness (L24) measured at 24 hours after blooming. The significance of the fixed effects and covariates were determined using the general linear model procedure of SAS. The final fixed effects models included contemporary group, sex and birthday deviation as a covariate. The residual from the above adjustment was used as the phenotype for the GEBV model development. The software GEBV was used to calculate direct genomic values (DGV), using the GBLUP methodology. To evaluate the accuracy of genomic prediction, two sets of animals were formed based on birth year: training (birth years: 2010, 2011 and 2012) and validation (birth year: 2013) populations. The accuracies for the three traits ranged from 0.29 to 0.33. Even though the accuracies were low, considering the costs and difficulty to measure and to select for meat quality traits, genomic selection might be a viable alternative.

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