298 Gut Microbiome Provides A New Source of Variation to Improve Growth Efficiency in Crossbred Pigs. (7th December 2018)

• Record Type: Journal Article
• Authors: Lu, D; Tiezzi, F; Maltecca, C
• Is Part Of: Journal of animal science. Volume 96(2018)Supplement 3
• Page Start: 112
• Page End: 113
• Publication Date: 2018-12-07
• Subjects: Pig -- Microbiome -- Efficiency; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/sky404.247
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: Gut microbiome has long been proven to affect pork production via nutritional, physiological, and immunological processes. We studied host genetics – gut microbiome relationship in pigs, seeking to incorporate such relationship in genetic imrpovement of pigs. There were 1205, 1295, and 1283 rectal samples collected at weaning (18.6 ± 1.09 days), 15 weeks post weaning (118.2 ± 1.18 days), and end of feeding trial (196.4 ± 7.86 days), respectively. There were 1039 animals having samples collected at all 3 time points. Analyses were performed at operational taxonomic unit (OTU) level, including 1755 OTUs. The animals were also gentoyped with the Illumina PorcineSNP60 Beadchip. Our association analyses identified 131 OTUs with large contribution to the total variance of backfat (BF), live weight (WT), and loin depth (LD), at week 14, 18, and 22, for each phenotypic record. Three OTUs (17, 758, and 1163) explained the largest proportion of the trait variance. Heritabilities of the 3 OTUs varied between 0.13 ± 0.05 and 0.40 ± 0.06 for OTU17, 0.02 ± 0.03 and 0.20 ± 0.06 for OTU758, 0.02 ± 0.03 and 0.21 ± 0.06 for OTU1163. Single nucleotide polymorphisms (SNPs) that had consistently large effects on OTU17 and OTU758, at week 15 and end of test, were identified on chromosomes 3, 6, and 7. Using microbiome data in estimating breeding values (BV) for BF and average daily weight gain (ADG) at 22 weeks post weaning, we found that providing the microbiome information, under the form of relatedness among individuals based on similarity of microbial communities, significantly improved the model fit for both BF and ADG, as well as reduced standard error of prediction for the BVs. This analysis was one of our preliminary attempts to working out a direction for using gut microbiome data in improving the accuracy of BVs in the pork industry.