Prolactin is an anterior pituitary hormone involved in various physiological phenomenon including reproduction. The prolactin receptor (PRLR) is detected in diverse tissues such as brain, ovary, placenta and uterus in several mammalian species. A total of 227 pigs [Korean native pigs (KNP) 27; Landrace pigs 29; Korean native pigs x Landrace F1 91; Nanchuckmacdon pigs 80] were used to investigate the allele frequency difference of the prolactin receptor (PRLR) gene among the four pig lines. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) with Alu I restriction enzyme was used to determine the genotypes of PRLR. Frequencies of PRLR alleles among the four different pig lines were not significantly different (Chi-square=3.94, DF=3, P=0.27). A total of 40 Nanchuckmacdon pigs were used to investigate the effect of the prolactin receptor (PRLR) gene on total number of piglets born (TNB), number of piglets of alive (NBA) using general linear model implemented in MINITAB software. For TNB, the AB genotype had higher genotypic value (10.61) than the values of AA (9.83) and BB (10.30). Likewise, the AB genotype had higher genotypic value (8.96) than the values of AA (8.18) and BB (8.90) for NBA. However, these associations of the PRLR gene with TNB and NBA were not statistically significant. In conclusion, it is necessary to increase the sample size for investigating the effect of the PRLR gene on TNB and NBA in pigs.

Blood types in pigs are divided into two types, A and O type. It is important to select and breed O-type pigs that have no hematologic rejection, because the blood type of the donor is an important factor causing immune rejection in xenotransplantation. Therefore, the gene that determines the blood type is GGTA1(glycoprotein, alpha-1,3-galactosyltransferase 1), which generally belongs to the ABO blood group. This study was carried out to develop a simple and accurate method by analyzing the structure of GGTA1 gene which determines blood type. A primer was designed to allow easy identification of the blood type of the target in the first and second deletion regions of intron 7 to distinguish between the A and O genotypes. That is, for the purpose of identifying the blood type using length difference after the PCR, the forward and reverse primers were designed in the highly conservative region. As a result, a pair of primers were prepared and PCR amplification was performed to distinguish three types of genotypes, AA, AO, and OO, using the length difference by electrophoresis. Using the above primers, the parents and their offspring were compared with each other to confirm the correct genetic pattern. And, in four pig breeds, the genes were amplified and the genotype could be correctly identified. In this study, we could diagnose the blood type of AA, AO, OO genotype of pigs by using primer of INDEL region. Especially, since it is possible to diagnose the genotype by the length difference, it is possible to diagnose it quickly and accurately from the gene amplification to the genotype reading

Growth traits, such as body weight, directly influence productivity and economic efficiency in the swine industry. In this study, we estimate heritability for body weight traits usinginformation from pedigree and genome-wide single nucleotide polymorphism (SNP) chip data. Four body weight phenotypes were measured in 1,105 F2 progeny from an intercross between Landrace and Jeju native black pigs. All experimental animals were subjected to genotypic analysis using PorcineSNP60K BeadChip platform, and 39,992 autosomal SNP markers filtered by quality control criteria were used to construct genomic relationship matrix for heritability estimation. Restricted maximum likelihood estimates of heritability were obtained using both genomic- and pedigree- relationship matrix in a linear mixed model. The heritability estimates using SNP information were smaller (0.36-0.55) than those which were estimated using pedigree information (0.62-0.97). To investigate effect of common environment, such as maternal effect, on heritability estimation, we included maternal effect as an additional random effect term in the linear mixed model analysis. We detected substantial proportions of phenotypic variance components were explained by maternal effect. And the heritability estimates using both pedigree and SNP information were decreased. Therefore, heritability estimates must be interpreted cautiously when there are obvious common environmental variance components.