The Genetics of Feed Efficiency and Feeding Behavior in Pigs

The overall objective of this research was to study the genetics of feed efficiency and feeding behavior with the use of feed intake measures recorded by electronic feeding system. The first study aimed at determining if two alternative implementations (termed MI and MICE) of multiple imputation were more effective to adjust errors occurring in feed intake collected by electronic feeders than the well-established linear mixed model (LMM) approach. In our results, multiple imputation outperformed the LMM approach in all simulated scenarios with mean accuracies of 96.71%, 93.45% and 90.24% obtained with MI and 96.84%, 94.42% and 90.13% with MICE, compared to 91.0%, 82.63% and 68.69% using LMM, for daily feed intake. In the second study we investigated measures of intake and growth, to determine the potential of genomic information in improving the efficiency of swine production. Magnitudes of heritability from pedigree analysis were moderate for growth, feed intake and ultrasound traits; heritability estimates were 0.32 +/- 0.09 for FCR (feed conversion ratio) but only 0.10 +/- 0.05 for RFI (residual feed intake). Comparatively, heritability estimates using marker information by Bayes-A models were about half of that from pedigree analysis, suggesting "missing heritability". Moderate positive genetic correlations between growth and feed intake (0.32 +/- 0.05), backfat (0.22 +/- 0.04), as well as, negative genetic correlations between growth and feed efficiency indicate selection solely on growth may lead to undesirable increases in feed intake, backfat and reduced feed efficiency. Accuracies of genomic prediction ranged from 9.4% for RFI to 36.5% for backfat, providing new insight into pig breeding and future selection programs using genomic information. The use of molecular information to dissect the genetic architecture underlying efficient growth in pigs was the subject of the third study. A region (166-140 Mb) on SSC 1, approximately 8 Mb upstream MC4R gene, was significantly associated with ADFI, ADG and backfat, where SOCS6 and DOK6 are proposed as the most likely candidate genes. Another region affecting weaning weight was identified on SSC 4 (84-85 Mb), harboring genes previously found to influence both human and cattle height: PLAG1, CHCHD7, RDHE2, MOS, RPS20, LYN and PENK. The fourth study aimed at dissecting different measures of feed efficiency in their relationship with feeding behavior and growth, exploring the use of efficient methods for the prediction of genomic breeding values, and accounting for the social interactions among individuals. Non-heritable social interaction has been observed for traits associated with measures recorded by electronic feeders and it is suggested that there is a need to include those effects to reduce bias for genetic parameter estimation when the variance explained by social interaction has been found significant. After accounting for social interaction, RG (residual growth) and RIG (combined measure of RFI and RG) have been found as two good measures of feed efficiency due to their moderate heritability and strong genetic correlation with other production traits. Feeding behavior traits were found moderately heritable and some were highly correlated with feed efficiency, which are worth further investigation. Increased accuracies have been shown when apply single-step GBLUP over BLUP for feeding behavior, feed efficiency, growth and off-test traits in a validation setting. Further research has been carried out to identify the underlying genetic regions affecting measures of feed efficiency and feeding behavior. Genomic regions have been identified for ANVD (average daily number of visits), AOTV (average occupation time per day) and FCR and candidate genes of those significant regions and regions approaching significant threshold for RG and RIG have been annotated. Finally, gene networks for all candidate genes located were built to investigate the relationships among genes in common pathways.