To understand molecular genetic characteristics of Korean pigs, the genetic relationships of nine pig breeds including two Korean pigs (Korean native pig and Korean wild pig), three Chinese pigs (Min pig, Xiang pig, and Wuzhishan pig), and four European breeds (Berkshire, Duroc, Landrace, and Yorkshire) were characterized from a 16-microsatellite loci analysis. The mean heterozygosity within breeds ranged from 0.494 to 0.703. Across multiple loci, significant deviation from Hardy-Weinberg equilibrium was observed in most pig breeds, except for two Chinese pigs (Min pig and Wuzhishan pig). This deviation was in the direction of heterozygote deficit. Across population loci, 36 of 144 significantly deviated (P < 0.05) from Hardy-Weinberg equilibrium. The mean FST, a measure of genetic divergence among subpopulations, of all loci indicated that 26.1% of total variation could be attributed to the breed difference. Relationship trees based on the Nei's DA genetic distance and scatter diagram from principal component analysis consistently displayed pronounced genetic differentiation among the Korean wild pig, Xiang pig, and Wuzhishan pig. Individual assignment test using a Bayesian method showed 100% success in assigning Korean and Chinese individual pigs into their correct breeds of origin and 100% exclusion success from all alternative reference populations at P < 0.001. These findings indicate that the Korean native pig has been experiencing progressive interbreeding with Western pig breeds after originating from a North China pig breed with a black coat color. Considering the close genetic relationship of Korean pigs to the Western breeds such as Berkshire and Landrace, our findings can be used as valuable genetic information for the preservation and further genetic improvement of the Korean native pig.

This study was conducted to estimate phenotypic and genetic parameters of body condition score (BCS) and reproductive traits in Hanwoo cows. DFREML procedures were applied to obtain variance-covariance components and heritability estimates with single or two-trait models. Estimates of phenotypic correlations of BCS at service with BCS at calving was 0.16 and 0.26 with calving interval, 0.08 with gestation length, and 0.06 with number of services per conception, respectively. Estimates of phenotypic correlation of BCS at calving was 0.10 with calving interval, 0.13 with gestation length, and 0.10 with number of services per conception, respectively. Estimates of phenotypic correlation were low and negative, -0.11 between calving interval and gestation length and -0.13 between gestation length and number of services per conception. Estimates of direct genetic correlation were -0.06, between BCS at service and BCS at calving, 0.37 between BCS at service and BCS at weaning, and -0.18 between BCS at calving and BCS at weaning. Estimates of direct genetic correlation of days from calving to the 1st service were 0.17 with number of services per conception and -0.21 with BCS at service. Estimates of direct genetic correlation for BCS at calving were -0.02 with number of services per conception and -0.08 with BCS at service. Estimates of direct genetic correlation for BCS at weaning were 0.02 with number of services per conception and -0.07 with BCS at service. Estimates of direct heritability from single trait analyses were 0.13 for BCS at service, 0.20 for BCS at calving, 0.02 for BCS at weaning, and 0.20 for number of service per conception, respectively. Estimates of direct heritability were 0.20 for birth weight and 0.10 for weaning weight.