Genome-wide association study for T lymphocyte subpopulations in swine.

BACKGROUND: Lymphocytes act as a major component of the adaptive immune system, taking very crucial responsibility for immunity. Differences in proportions of T-cell subpopulations in peripheral blood among individuals under same conditions provide evidence of genetic control on these traits, but little is known about the genetic mechanism of them, especially in swine. Identification of the genetic control on these variants may help the genetic improvement of immune capacity through selection. RESULTS: To identify genomic regions responsible for these immune traits in swine, a genome-wide association study was conducted. A total of 675 pigs of three breeds were involved in the study. At 21 days of age, all individuals were vaccinated with modified live classical swine fever vaccine. Blood samples were collected when the piglets were 20 and 35 days of age, respectively. Seven traits, including the proportions of CD4+, CD8+, CD4+CD8+, CD4+CD8-, CD4-CD8+, CD4-CD8- and the ratio of CD4+ to CD8+ T cells were measured at the two ages. All the samples were genotyped for 62,163 single nucleotide polymorphisms (SNP) using the Illumina porcineSNP60k BeadChip. 40833 SNPs were selected after quality control for association tests between SNPs and each immune trait considered based on a single-locus regression model. To tackle the issue of multiple testing in GWAS, 10,000 permutations were performed to determine the chromosome-wise and genome-wise significance levels of association tests. In total, 61 SNPs with chromosome-wise significance level and 3 SNPs with genome-wise significance level were identified. 27 significant SNPs were located within the immune-related QTL regions reported in previous studies. Furthermore, several significant SNPs fell into the regions harboring known immunity-related genes, 14 of them fell into the regions which harbor some known T cell-related genes. CONCLUSIONS: Our study demonstrated that genome-wide association studies would be a feasible way for revealing the potential genetics variants affecting T-cell subpopulations. Results herein lay a preliminary foundation for further identifying the causal mutations underlying swine immune capacity in follow-up studies.

Comparison of five methods for genomic breeding value estimation for the common dataset of the 15th QTL-MAS Workshop.

BACKGROUND: Genomic breeding value estimation is the key step in genomic selection. Among many approaches, BLUP methods and Bayesian methods are most commonly used for estimating genomic breeding values. Here, we applied two BLUP methods, TABLUP and GBLUP, and three Bayesian methods, BayesA, BayesB and BayesCπ, to the common dataset provided by the 15th QTL-MAS Workshop to evaluate and compare their predictive performances. RESULTS: For the 1000 progenies without phenotypic values, the correlations between GEBVs by different methods ranged from 0.812 (GBLUP and BayesCπ) to 0.997 (TABLUP and BayesB). The accuracies of GEBVs (measured as correlations between true breeding values (TBVs) and GEBVs) were from 0.774 (GBLUP) to 0.938 (BayesCπ) and the biases of GEBVs (measure as regressions of TBVs on GEBVs) were from 1.033 (TABLUP) to 1.648 (GBLUP). The three Bayesian methods and TABLUP had similar accuracy and bias. CONCLUSIONS: BayesA, BayesB, BayesCπ and TABLUP performed similarly and satisfactorily and remarkably outperformed GBLUP for genomic breeding value estimation in this dataset. TABLUP is a promising method for genomic breeding value estimation because of its easy computation of reliabilities of GEBVs and its easy extension to real life conditions such as multiple traits and consideration of individuals without genotypes.

Genome-wide association analyses of the 15th QTL-MAS workshop data using mixed model based single locus regression analysis.

BACKGROUND: The mixed model based single locus regression analysis (MMRA) method was used to analyse the common simulated dataset of the 15th QTL-MAS workshop to detect potential significant association between single nucleotide polymorphisms (SNPs) and the simulated trait. A Wald chi-squared statistic with df =1 was employed as test statistic and the permutation test was performed. For adjusting multiple testing, phenotypic observations were permutated 10,000 times against the genotype and pedigree data to obtain the threshold for declaring genome-wide significant SNPs. Linkage disequilibrium (LD) in term of D' between significant SNPs was quantified and LD blocks were defined to indicate quantitative trait loci (QTL) regions. RESULTS: The estimated heritability of the simulated trait is approximately 0.30. 82 genome-wide significant SNPs (P < 0.05) on chromosomes 1, 2 and 3 were detected. Through the LD blocks of the significant SNPs, we confirmed 5 and 1 QTL regions on chromosomes 1 and 3, respectively. No block was detected on chromosome 2, and no significant SNP was detected on chromosomes 4 and 5. CONCLUSION: MMRA is a suitable method for detecting additive QTL and a fast method with feasibility of performing permutation test. Using LD blocks can effectively detect QTL regions.

A genome-wide association study identifies two novel promising candidate genes affecting Escherichia coli F4ab/F4ac susceptibility in swine.

Enterotoxigenic Escherichia coli (ETEC) expressing F4 fimbria is the major pathogenic bacteria causing diarrhoea in neonatal and post-weaning piglets. Previous studies have revealed that the susceptibility to ETEC F4ab/F4ac is an autosomal Mendelian dominant trait and the loci controlling the F4ab/F4ac receptor are located on SSC13q41, between markers SW207 and S0283. To pinpoint these loci and further validate previous findings, we performed a genome-wide association study (GWAS) using a two generation family-based population, consisting of 301 piglets with phenotypes of susceptibility to ETEC F4ab/F4ac by the vitro adhesion test. The DNA of all piglets and their parents was genotyped using the Illumina PorcineSNP60 BeadChip, and 50,972 and 50,483 SNPs were available for F4ab and F4ac susceptibility, respectively, in the association analysis after quality control. In summary, 28 and 18 significant SNPs (p<0.05) were detected associated with F4ab and F4ac susceptibility respectively at genome-wide significance level. From these significant findings, two novel candidate genes, HEG1 and ITGB5, were firstly identified as the most promising genes underlying F4ab/F4ac susceptibility in swine according to their functions and positions. Our findings herein provide a novel evidence for unravelling genetic mechanism of diarrhoea risk in piglets.