Analysis of public single nucleotide polymorphisms in commercial pig populations

Analyses of porcine public SNPs in coding-gene regions by re-sequencing and phenotypic association studies

The Porcine SNP database has a huge number of SNPs, but these SNPs are mostly found by computer data-mining procedures and have not been well characterized. We re-sequenced 1,439 porcine public SNPs from four commercial pig breeds and one Korean domestic breed (Korean Native pig, KNP) by using two DNA pools from eight unrelated animals in each breed. These SNPs were from 419 protein-coding genes covering the 18 autosomes, and the re-sequencing in breeds confirmed 690 public SNPs (47.9%) and 226 novel mutations (173 SNPs and 53 insertions/deletions). Thus, totally, 916 variations were found from our study. Of the 916 variations, 148 SNPs (16.2%) were found across all the five breeds, and 199 SNPs (21.7%) were breed specific polymorphisms. According to the SNP locations in the gene sequences, these 916 variations were categorized into 802 non-coding SNPs (785 in intron, 17 in 3'-UTR) and 114 coding SNPs (86 synonymous SNPs, 28 non-synonymous SNPs). The nucleotide substitution analyses for these SNPs revealed that 70.2% were from transitions, 20.0% from transversions, and the remaining 5.79% were deletions or insertions. Subsequently, we genotyped 261 SNPs from 180 genes in an experimental KNP × Landrace F2 cross by the Sequenom MassARRAY system. A total of 33 traits including growth, carcass composition and meat quality were analyzed for the phenotypic association tests using the 132 SNPs in 108 genes with minor allele frequency (MAF)>0.2. The association results showed that five marker-trait combinations were significant at the 5% experiment-wise level (ADCK4 for rear leg, MYH3 for rear leg, Hunter B, Loin weight and Shearforce) and four at the 10% experiment-wise level (DHX38 for average daily gain at live weight, LGALS9 for crude lipid, NGEF for front leg and LIFR for pH at 24 h). In addition, 49 SNPs in 44 genes showing significant association with the traits were detected at the 1% comparison-wise level. A large number of genes that function as enzymes, transcription factors or signalling molecules were considered as genetic markers for pig growth (RNF103, TSPAN31, DHX38, ABCF1, ABCC10, SCD5, KIAA0999 and FKBP10), muscling (HSPA5, PTPRM, NUP88, ADCK4, PLOD1, DLX1 and GRM8), fatness (PTGIS, IDH3B, RYR2 and NOL4) and meat quality traits (DUSP4, LIFR, NGEF, EWSR1, ACTN2, PLXND1, DLX3, LGALS9, ENO3, EPRS, TRIM29, EHMT2, RBM42, SESN2 and RAB4B). The SNPs or genes reported here may be beneficial to future marker assisted selection breeding in pigs.

Reporting 678 putative cSNPs from full-length enriched cDNA sequences of the Korean native pig

Sequences from the clones of full-length enriched cDNA libraries serve as valuable resources for functional genomic studies. We have analysed 1970 high-quality chromatograms (Phred value >or= 30) that were obtained from sequencing the 5' ends of brainstem, liver, neocortex and spleen clones derived from full-length enriched cDNA libraries from Korean native pigs. In addition, 50,000 pig expressed sequence tag (EST) sequence trace files were obtained from Genbank and combined with our sequencing information to facilitate SNP identification in silico. The process generated 8118 contigs, of which 239 included minimum one sequence from Korean native pig and contained 678 putative coding single nucleotide polymorphisms (cSNPs). Of these, 33 putative cSNPs were randomly selected for confirmatory analysis and validated using 20 pigs from four different breeds (Duroc, Landrace, Yorkshire, Korean native pig). Of the 33 putative cSNPs, 20 were confirmed (61%), which was similar to the frequency reported in other studies. We also identified 15 new cSNPs from the validation process, which were not detected by our in silico analysis. Our study shows that analysing genetically diverse pig breeds including the Korean native pig could serve as a useful strategy for generating a large number of cSNPs.