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Genome wide association studies (GWAS) are being extensively used in revealing genetic architecture of complex traits. However, GWAS offer limited understanding of the biological role of significant single nucleotide polymorphisms (SNPs) affecting complex traits. Pathway analysis using GWAS results is an important step where we firstly detect genes located near GWAS-detected SNPs and subsequently we detect enrichment of these genes in various biological processes and pathways. The objective of this study was to apply these steps to identify relevant pathways involved in residual feed intake (RFI) in pigs. Residual feed intake is a feed efficiency measure and is highly economically important in animal production. In our study, a total of 596 Yorkshire boars had phenotypic and genotypic records. After quality control, 37,915 SNPs were available for GWAS which was implemented in the DMU software package. Genome wide association analysis detected 3,450 SNPs (P < 0.05) significantly associated with this trait. Using the R-NCBI2R package, 7,169 nearby genes were found in 0.5 Mb flanking the SNP positions for all 3,450 SNPs. Among them, 2,934 genes were functionally recognized in pigs and were used as input in Database for Annotation, Visualization and Integrated Discovery (DAVID). Neuroactive ligand-receptor interaction, SNARE interactions in vesicular transport, pyruvate metabolism and Wnt signaling pathway were detected by using KEGG tools, growth hormone and phospholipase C signaling pathway were detected by using BioCarta pathway analysis tools and asynaptic_vesicle_trafficking and thyrotropin-releasing hormone receptor signaling pathways were identified by using Panther-pathway profiling tools. Several of these pathways such as Wnt, growth hormone and thyrotropin-releasing hormone receptor signaling pathway are known to be involved in biological processes closely related to regulation of feed intake or residual feed intake. These results provide insights into the genetic architecture as well as the systems biological mechanisms of this complex trait in pigs.

Feed efficiency and feeding behavior traits are economically important traits in pig production. The objective of this study was to identify genetic variants and mechanisms affecting daily feed intake (DFI) and feeding behavior traitsin Duroc (DD), Landrace (LL) and Yorkshire (YY) pig breeds, via Genome Wide Association Studies (GWAS) and systems genetics methods

This study was aimed at identifying genomic regions controlling feeding behaviors inDanish Duroc boars and its potential implications for eating behaviors in humans.Individual daily feed intake (DFI), total daily time spent in feeder (TPD), number of dailyvisits to feeder (NVD), time spent to eat per visit (TPV), mean feed intake per visit(FPV) and mean feed intake rate (FR) were available on 1130 boars. All boars weregenotyped using the Illumina Porcine SNP60 BeadChip. The association analyseswere performed using the GenABEL package in R. Sixteen SNPs had moderategenome-wide significant (p < 5E-05) and 76 SNPs had suggestive (p < 5E-04)association with feeding behavior traits. Locus M1GA0016584 located close to theMSI2 gene on chromosome (SSC) 14 was very strongly associated with NVD (p =9.6E-07). Thirty six SNPs were located in genome regions where QTLs havepreviously been reported for behaviors and/or feed intake traits in pigs. The regions:64-65Mb on SSC 1, 124-130Mb on SSC 8, 63-68Mb on SSC 11, 32-39Mb and 59-60Mb on SSC 12 harbored several significant SNPs. Three and two haplotypes thatwere detected in significant regions on SSC1 and SSC12 affected DFI and NVD,respectively. Synapse, dephosphorylation and positive regulation of peptide secretiongenes were found highly significantly associated with feeding behavior traits byfunctional annotation. This is the first GWAS to identify genetic variants and biologicalmechanisms for feeding behavior in pigs and these results are important for geneticimprovement of pig feed efficiency. The results of pig-human comparative genemapping revealed some important genomic regions and/or genes on the humangenome that may influence eating behavior in human and consequently affect thedevelopment of obesity and metabolic syndromes. This is the first such translationalgenomics study to report potential candidate genes for eating behavior in humans

This aim of this study was to identify genomic regions controlling feed efficiency defined by 2 estimated residual feed intake (RFI) measures in Danish Duroc boars. RFI1 was calculated based on regression of individual average daily feed intake (30-100 kg) on initial test weight and average daily gain (30-100 kg). RFI2 was the same as RFI1 except that it was also regressed on backfat (BF). A total of 868 boars had phenotypic and genotype (i.e. Illumina Porcine SNP60 BeadChip) records. A total of 33945 SNPs were available for genome wide association studies (GWAS) after quality control. Deregressed EBVs were used as response variables in GWAS implemented in the R-GenABEL package. A total of 16 and 17 loci were significantly associated (p < 5×10-4) with RFI1 and RFI2, respectively. 12 SNPs were in common implying the existence of common genetic mechanisms. A mutation (A/G) at locus ALGA0098358 on CPVL gene on SSC18 was highly associated with both RFI1 (p = 1.8×10-4) and RFI2 (p = 4.5×10-5). Moreover, the genomic region 30.5-31.5Mb on SSC1 contained high numbers of significant SNPs (8 loci) for both RFIs. The SNPs within region of MAP3K5 on SSC1, GTF2IRD2 on SSC3, and WDR70 on SSC16 may be interesting markers for both RFIs. The ANKRD6 on SSC1, CADM1 on SSC9 and RHBDD1 on SSC15 were distinct markers for each RFI1 and RFI2, respectively. Further systems genetics investigations were carried out to reveal functional importance of genes and haplotypes on candidate chromosomes with high numbers of significant SNPs. This study enhanced our biological knowledge of the genes and variants controlling RFIs and might contribute to genetic improvement for feed efficiency traits in pigs

The objective of this study was to develop random regression models and estimate covariance functions for daily feed intake (DFI) in Danish Duroc pigs. A total of 476201 DFI records were available on 6542 Duroc boars between 70 to 160 days of age. The data originated from the National test station and were collected using ACEMO electronic feeders in the period of 2008 to 2011. The pedigree was traced back to 1995 and included 17222 animals. The phenotypic feed intake curve was decomposed into a fixed curve, being specific to the barn-year-season effect and curves associated with the random pen-year-season, permanent, and animal genetic effects. The functional form was based on Legendre polynomials. A total of 64 models for random regressions were initially ranked by BIC to identify the approximate order for the Legendre polynomials using AI-REML. The parsimonious model included Legendre polynomials of 2nd order for genetic and permanent environmental curves and a heterogeneous residual variance, allowing the daily residual variance to change along the age trajectory due to scale effects. The parameters of the model were estimated in a Bayesian framework, using the RJMC module of the DMU package, where weakly informative priors were derived from preliminary AI-REML analysis. We used a burn-in of 10k followed by 90k rounds, interleaving every 10th sample. Posterior mean heritabilities were low for DFI, but increased from 0.07 to 0.12 at 100 days of age and then decreased fluctuating to around 0.08. The low heritabilities were due to a higher residual variance when using individual DFI records compared to average DFI records over the entire test period. The heritability of DFI for the entire test period was 0.28, corresponding closely to the estimate derived from analysis of average DFI records. Eigenvalues of the genetic covariance function showed that 33% of genetic variability was explained by the individual genetic curve of the pigs. This proportion was covered by linear (27%) and quadratic (6%) coefficients. Genetic eigenfunctions revealed that altering the shape of the feed intake curve by selection may be an option in Danish Duroc pigs