Linkage disequilibrium (LD) across the genome is critical information for association studies and genomic selection because it determines the number of SNP that should be used for a successful association analysis and genomic selection. Linkage disequilibrium also influences the accuracy of genomic breeding values. Some studies have demonstrated that SNP in strong LD are organized into discrete blocks of haplotypes, which are separated by possibly hot spots of recombination. To reduce the number of markers needed to be genotyped for association mapping, a set of SNP can be selected that labels all haplotype blocks. We estimated the LD, calculated the average haplotype block size for 6 pig lines, and compared the block size between lines. Six commercial pig lines were genotyped using the Illumina PorcineSNP60 (number of markers M = 62,163) Genotyping BeadChip (Illumina Inc.); on average, a panel of 37,623 SNP with an average minor allelic frequency (MAF) of 0.283 was included in the analysis. The LD declined as a function of distance. All pig lines had an average r(2) above 0.3 for markers 100 to 150 apart. The estimated average block size was 394.885 kb, and blocks between 100 and 400 kb were most prominent (49.96%) in all lines. These results showed that the extent of LD in pigs is much larger than in the cattle population, in accordance with the genetic map length of pigs, which is much shorter than cattle. The evaluated lines have 2,640 to 3,037 blocks, covering 45% of the pig genome, on average. Differences in haplotype block size between lines were observed for some chromosomes (i.e., SSC 3, 5, 7, 13, 14, and 18), which provide a direction for future studies of haplotype block conservation or divergence across lines.

Seventy-two pigs of three genetic groups (Brazilian indigenous breed Piau, Commercial line and Crossbred) of both sexes were slaughtered at four live weights (30, 60, 90 and 120 kg). Intramuscular fat (IMF) content in Longissimus dorsi muscle of each animal was extracted and correlated with candidate gene mRNA expression (ATN1, EEF1A2, FABP3, LDLR, MGP, OBSCN, PDHB, TRDN and RYR1). Within slaughter weight of 120 kg, Piau and Crossbred pigs showed higher IMF content (p < 0.05) than commercial animals, with 2.48, 2.08 and 1.00% respectively. Barrows presented higher values of IMF (p < 0.05) than gilts (1.54 and 1.30% respectively). Gene expression of EEF1A2, FABP3, LDLR, OBSCN, PDHB, TRDN and RYR1 were correlated with IMF (p < 0.05) using the whole dataset. For Piau data only, expression of FABP3, LDLR, MGP, OBSCN, PDHB, TRDN and RYR1 showed correlation with IMF (p < 0.05). Genes that have important roles in lipid transportation inside the cell (FABP3) and tissues (LDLR) showed correlation with IMF of, respectively, 0.68 and 0.63 using the whole data set, and 0.90 and 0.91 using data from Piau animals. The highly positive correlation of the LDLR and FAPB3 expression with IMF content may confirm that these genes are important for fat deposition in the porcine L. dorsi muscle.

BackgroundGenomic selection and genomic wide association studies are widely used methods that aim to exploit the linkage disequilibrium (LD) between markers and quantitative trait loci (QTL). Securing a sufficiently large set of genotypes and phenotypes can be a limiting factor that may be overcome by combining data from multiple breeds or using crossbred information. However, the estimated effect of a marker in one breed or a crossbred can only be useful for the selection of animals in another breed if there is a correspondence of the phase between the marker and the QTL across breeds. Using data of five pure pig (Sus scrofa) lines (SL1, SL2, SL3, DL1, DL2), one F1 cross (DLF1) and two commercial finishing crosses (TER1 and TER2), the objectives of this study were: (i) to compare the equality of LD decay curves of different pig populations; and (ii) to evaluate the persistence of the LD phase across lines or final crosses.ResultsAlmost all of the lines presented different extents of LD, except for the SL2 and DL3, both of which exhibited the same extent of LD. Similar levels of LD over large distances were found in crossbred and pure lines. The crossbred animals (DLF1, TER1 and TER2) presented a high persistence of phase with their parental lines, suggesting that the available porcine single nucleotide polymorphism (SNP) chip should be dense enough to include markers that have the same LD phase with QTL across crossbred and parental pure lines. The persistence of phase across pure lines varied considerably between the different line comparisons; however, correlations were above 0.8 for all line comparisons when marker distances were smaller than 50 kb.ConclusionsThis study showed that crossbred populations could be very useful as a reference for the selection of pure lines by means of the available SNP chip panel. Here, we also pinpoint pure lines that could be combined in a multiline training population. However, if multiline reference populations are used for genomic selection, the required density of SNP panels should be higher compared with a single breed reference population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-014-0126-3) contains supplementary material, which is available to authorized users.

This study aimed to compare two different Genome-Wide Selection (GWS) methods (Ridge Regression BLUP À RR-BLUP and Bayesian LASSO À BL) to predict the genomic estimated breeding values (GEBV) of four phenotypes, including two boar taint compounds, i.e., the concentrations of androstenone (andro) and skatole (ska), and two carcass traits, i.e., backfat thickness (fat) and loin depth (loin), which were measured in a commercial male pig line. Six hundred twenty-two boars were genotyped for 2,500 previously selected single nucleotide polymorphisms (SNPs). The accuracies of the GEBV using both methods were estimated based on Jack-knife cross-validation. The BL showed the best performance for the andro, ska and loin traits, which had accuracy values of 0.65, 0.58 and 0.33, respectively; for the fat trait, the RR-BLUP accuracy of 0.61 outperformed the BL accuracy of 0.56. Considering that BL was more accurate for the majority of the traits, this method is the most favoured for GWS under the conditions of this study. The most relevant SNPs for each trait were located in the chromosome regions that were previously indicated as QTL regions in other studies, i.e., SSC6 for andro and ska, SSC2 for fat, and SSC11, SSC15 and SSC17 for loin.