Genomic evaluation using SNP- and haplotype-based genomic relationship matrices in a closed line of Duroc pigs.

A simulation analysis and real phenotype analysis were performed to evaluate the impact of three different relationship matrices on heritability estimation and prediction accuracy in a closed-line breeding of Duroc pigs. The numerator relationship matrix (NRM), single nucleotide polymorphism (SNP)-based genomic relationship matrix (GRM) (GS ), and haplotype-based GRM (GH ) were applied in this study. We used PorcineSNP60 genotype array data (38 114 SNPs) of 831 Duroc pigs with four selection traits. In both heritability estimation and prediction accuracy, the accuracy depended on the number of animals with records. For heritability estimation, a large difference in the results among three relationship matrices was not shown, but the trend of the estimated heritabilities between GRMs, that is GS  < GH , was shown in this population. For the accuracy of prediction values in test animals, the accuracies of prediction values obtained by two GRMs were higher than that by the NRM in this population. The accuracies obtained by GRMs using animals with no records were lower than that by the NRM using animals with their performance records, but were close to that by the NRM using animals with full-sib testing records.

Genome-wide association studies reveal additional related loci for fatty acid composition in a Duroc pig multigenerational population.

The aim of the present study was to detect quantitative trait loci affecting fatty acid composition in back fat and intramuscular fat in a Duroc pig population comprising seventh-generation pedigrees using genome-wide association studies (GWAS). In total, 305 animals were genotyped using single nucleotide polymorphisms (SNPs) array and five selected SNPs from regions containing known candidate genes related to fatty acid synthesis or metabolism. In total, 24 genome-wide significant SNP regions were detected in 12 traits, and 76 genome-wide suggestive SNP regions were detected in 33 traits. The Sus scrofa chromosome (SSC) 7 at 10.3 Mb was significantly associated with C17:0 in intramuscular fat, while the SSC9 at 13.6 Mb was significantly associated with C14:0 in intramuscular fat. The SSC12 at 1.0 Mb was significantly associated with C14:0 in back fat and the SSC14 at 121.0 Mb was significantly associated with C18:0 in intramuscular fat. These regions not only replicated previously reported loci containing some candidate genes involved in fatty acid composition (fatty acid synthase and stearoyl-CoA desaturase) but also included several additional related loci.

SNP- and haplotype-based genome-wide association studies for growth, carcass, and meat quality traits in a Duroc multigenerational population.

BACKGROUND: The aim of the present study was to compare the power of single nucleotide polymorphism (SNP)-based genome-wide association study (GWAS) and haplotype-based GWAS for quantitative trait loci (QTL) detection, and to detect novel candidate genes affecting economically important traits in a purebred Duroc population comprising seven-generation pedigree. First, we performed a simulation analysis using real genotype data of this population to compare the power (based on the null hypothesis) of the two methods. We then performed GWAS using both methods and real phenotype data comprising 52 traits, which included growth, carcass, and meat quality traits. RESULTS: In total, 836 animals were genotyped using the Illumina PorcineSNP60 BeadChip and 14 customized SNPs from regions of known candidate genes related to the traits of interest. The power of SNP-based GWAS was greater than that of haplotype-based GWAS in a simulation analysis. In real data analysis, a larger number of significant regions was obtained by SNP-based GWAS than by haplotype-based GWAS. For SNP-based GWAS, 23 genome-wide significant SNP regions were detected for 17 traits, and 120 genome-wide suggestive SNP regions were detected for 27 traits. For haplotype-based GWAS, 6 genome-wide significant SNP regions were detected for four traits, and 11 genome-wide suggestive SNP regions were detected for eight traits. All genome-wide significant SNP regions detected by haplotype-based GWAS were located in regions also detected by SNP-based GWAS. Four regions detected by SNP-based GWAS were significantly associated with multiple traits: on Sus scrofa chromosome (SSC) 1 at 304 Mb; and on SSC7 at 35-39 Mb, 41-42 Mb, and 103 Mb. The vertnin gene (VRTN) in particular, was located on SSC7 at 103 Mb and was significantly associated with vertebrae number and carcass lengths. Mapped QTL regions contain some candidate genes involved in skeletal formation (FUBP3; far upstream element binding protein 3) and fat deposition (METTL3; methyltransferase like 3). CONCLUSION: Our results show that a multigenerational pig population is useful for detecting QTL, which are typically segregated in a purebred population. In addition, a novel significant region could be detected by SNP-based GWAS as opposed to haplotype-based GWAS.