Abstract
The efficiency of producing salable products in the pork industry is largely determined by costs associated with feed and by the amount and quality of lean meat produced. The objectives of this paper were 1) to explore heritability and genetic correlations for growth, feed efficiency, and real-time ultrasound traits using both pedigree and marker information and 2) to assess accuracy of genomic prediction for those traits using Bayes A prediction models in a Duroc terminal sire population. Body weight at birth (BW at birth) and weaning (BW at weaning) and real-time ultrasound traits, including back fat thickness (BF), muscle depth (MD), and intramuscular fat content (IMF), were collected on the basis of farm protocol. Individual feed intake and serial BW records of 1,563 boars obtained from feed intake recording equipment (FIRE; Osborne Industries Inc., Osborne, KS) were edited to obtain growth, feed intake, and feed efficiency traits, including ADG, ADFI, feed conversion ratio (FCR), and residual feed intake (RFI). Correspondingly, 1,047 boars were genotyped using the Illumina PorcineSNP60 BeadChip. The remaining 516 boars, as an independent sample, were genotyped with a low-density GGP-Porcine BeadChip and imputed to 60K. Magnitudes of heritability from pedigree analysis were moderate for growth, feed intake, and ultrasound traits (ranging from 0.44 ± 0.11 for ADG to 0.58 ± 0.09 for BF); heritability estimates were 0.32 ± 0.09 for FCR but only 0.10 ± 0.05 for RFI. Comparatively, heritability estimates using marker information by Bayes A models were about half of those from pedigree analysis, suggesting "missing heritability." Moderate positive genetic correlations between growth and feed intake (0.32 ± 0.05) and back fat (0.22 ± 0.04), as well as negative genetic correlations between growth and feed efficiency traits (-0.21 ± 0.08, -0.05 ± 0.07), indicate selection solely on growth traits may lead to an undesirable increase in feed intake, back fat, and reduced feed efficiency. Genetic correlations among growth, feed intake, and FCR assessed by a multiple-trait Bayes A model resulted in increased genetic correlation between ADG and ADFI, a negative correlation between ADFI and FCR, and a positive correlation between ADG and FCR. Accuracies of genomic prediction for the traits investigated, ranging from 9.4% for RFI to 36.5% for BF, were reported that might provide new insight into pig breeding and future selection programs using genomic information.
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