Evaluation of Genome Based Estimated Breeding Values for Meat Quality in a Berkshire Population Using High Density Single Nucleotide Polymorphism Chips

Abstract

The accuracy of genomic estimated breeding values (GEBV) was evaluated for sixteen meat quality traits in a Berkshire population (n = 1,191) that was collected from Dasan breeding farm, Namwon, Korea. The animals were genotyped with the Illumina porcine 62 K single nucleotide polymorphism (SNP) bead chips, in which a set of 36,605 SNPs were available after quality control tests. Two methods were applied to evaluate GEBV accuracies, i.e. genome based linear unbiased prediction method (GBLUP) and Bayes B, using ASREML 3.0 and Gensel 4.0 software, respectively. The traits composed different sets of training (both genotypes and phenotypes) and testing (genotypes only) data. Under the GBLUP model, the GEBV accuracies for the training data ranged from 0.42±0.08 for collagen to 0.75±0.02 for water holding capacity with an average of 0.65±0.04 across all the traits. Under the Bayes B model, the GEBV accuracy ranged from 0.10±0.14 for National Pork Producers Council (NPCC) marbling score to 0.76±0.04 for drip loss, with an average of 0.49±0.10. For the testing samples, the GEBV accuracy had an average of 0.46±0.10 under the GBLUP model, ranging from 0.20±0.18 for protein to 0.65±0.06 for drip loss. Under the Bayes B model, the GEBV accuracy ranged from 0.04±0.09 for NPCC marbling score to 0.72±0.05 for drip loss with an average of 0.38±0.13. The GEBV accuracy increased with the size of the training data and heritability. In general, the GEBV accuracies under the Bayes B model were lower than under the GBLUP model, especially when the training sample size was small. Our results suggest that a much greater training sample size is needed to get better GEBV accuracies for the testing samples.

Comparison of genomic predictions for carcass and reproduction traits in Berkshire, Duroc and Yorkshire populations in Korea

“…In the Berkshire and Duroc populations, the BFT heritability estimates were 0.50 and 0.41, respectively. This result agreed with the previous reports [20,21], in which the estimated heritabilities of the trait ranged from 0.34 to 0.56 for the same breeds. For CWT, the estimated heritabilities of 0.25 to 0.43 for the three breeds fell within the range (0.13 to 0.43) of heritability estimates in previous reports [7,20].…”

Genetic parameter estimation and gene association analyses for meat quality traits in open‐air free‐range Iberian pigs

“…(2014), Baby et al. (2014) or Lee et al. (2015)) showed moderate‐high values (from 0.20 to 0.51); except Suzuki et al.…”

Genomic selection in pigs: state of the art and perspectives

“…Nevertheless the results of this study suffered from the selection design that aimed to evaluate and select crossbred lines through the use of phenotypes recorded in purebred animals. Another study included a total of 16 meat quality traits that were predicted with GBLUP and Bayes B models in about 1200 Berkshire pigs genotyped with the 60K Illumina SNP panel (Baby et al 2014). The accuracy of GEBV, calculated on the standard errors of GEBV, mainly depended on the heritability of the traits and the size of the training dataset that was different for each trait.…”

“…The accuracy of GEBV, calculated on the standard errors of GEBV, mainly depended on the heritability of the traits and the size of the training dataset that was different for each trait. Larger training sets were envisaged to increase the accuracy of GEBV to efficiently implement genomic selection in that population (Baby et al 2014). Finally, implementation of genomic selection is also expected for several other traits that might indirectly affect production efficiency, like pig welfare-relatedparameters such as sow longevity and behaviour.…”