Feed intake, average daily gain, feed efficiency, and real-time ultrasound traits in Duroc pigs: II. Genomewide association

Efficient use of feed resources has become a clear challenge for the U.S. pork industry as feed costs continue to be the largest variable expense. The availability of the Illumina Porcine60K BeadChip has greatly facilitated whole-genome association studies to identify chromosomal regions harboring g...

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Bibliographic Details
Published in:Journal of animal science 2014-07, Vol.92 (7), p.2846-2860
Main Authors: Jiao, S, Maltecca, C, Gray, K A, Cassady, J P
Format: Article
Language:English
Subjects:
Adiposity - genetics
Adiposity - physiology
Animal Feed
Animals
Digestion - genetics
Digestion - physiology
Eating - genetics
Eating - physiology
Feeds
Genome-Wide Association Study - veterinary
Genomics
Haplotypes - genetics
Hogs
Muscle, Skeletal - diagnostic imaging
Polymorphism, Single Nucleotide - genetics
Quantitative Trait Loci - genetics
Quantitative Trait, Heritable
Swine - genetics
Swine - growth & development
Swine - physiology
Ultrasonic imaging
Ultrasonography
Weight Gain - genetics
Weight Gain - physiology
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Summary:Efficient use of feed resources has become a clear challenge for the U.S. pork industry as feed costs continue to be the largest variable expense. The availability of the Illumina Porcine60K BeadChip has greatly facilitated whole-genome association studies to identify chromosomal regions harboring genes influencing those traits. The current study aimed at identifying genomic regions associated with variation in feed efficiency and several production traits in a Duroc terminal sire population, including ADFI, ADG, feed conversion ratio, residual feed intake (RFI), real-time ultrasound back fat thickness (BF), ultrasound muscle depth, intramuscular fat content (IMF), birth weight (BW at birth), and weaning weight (BW at weaning). Single trait association analyses were performed using Bayes B models with 35,140 SNP on 18 autosomes after quality control. Significance of nonoverlapping 1-Mb length windows (n = 2,380) were tested across 3 QTL inference methods: posterior distribution of windows variances from Monte Carlo Markov Chain, naive Bayes factor, and nonparametric bootstrapping. Genes within the informative QTL regions for the traits were annotated. A region ranging from166 to 140 Mb (4-Mb length) on SSC 1, approximately 8 Mb upstream of the MC4R gene, was significantly associated with ADFI, ADG, and BF, where SOCS6 and DOK6 are proposed as the most likely candidate genes. Another region affecting BW at weaning was identified on SSC 4 (84-85 Mb), harboring genes previously found to influence both human and cattle height: PLAG1, CHCHD7, RDHE2 (or SDR16C5), MOS, RPS20, LYN, and PENK. No QTL were identified for RFI, IMF, and BW at birth. In conclusion, we have identified several genomic regions associated with traits affecting nutrient utilization that could be considered for future genomic prediction to improve feed utilization.
ISSN:0021-8812
1525-3163
DOI:10.2527/jas.2014-7337