• Korean Journal of Organic Agriculture
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• v.12 no.2
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• pp.197-207
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• 2004

Identification of animals has been used with an e ar tag with dummy code and blood typing has been used for paternity and individual identification in live animals. Various genetic markers are different for breeds of pig and hence, it is necessary to identity the discrete genetic marker in korean native pig. A total of 240 pigs were used to find korean native pig population specific markers that expressed in population of korean native pigs. To identify the individual traceability, 20 animals were randomly chosen and tested for a whole process from being live to slaughter stages. The candidate genetic marker used in the study were 18 DNA microsatellites which were identified in pig genome. The number of alleles of those DNA microsatellites ranged form a minimum of 3 to maximum of 6. The heterozygote frequency rang6d from 0.44 to 0.69. Effective number of alleles for each DNA microsatellotes were 2 to 4. By choosing 6 candidate genetic markers among all, the traceability of individual identification was estimated as accurate as 99.99%(p>0.0014), nearly.

• Reproductive and Developmental Biology
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• v.37 no.4
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• pp.205-211
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• 2013

The swine is one of the most widespread mammalian throughout the whole world. Presently, many studies concerning microsatellites in swine, especially domestic pigs, have been carried out in order to investigate general diversity patterns among either populations or breeds. Until now, a lot of time and effort spend into a single PCR method. But simple and more rapid multiplex PCR methods have been developed. The purpose of this study is to develop a robust set of microsatellites markers (MS marker) for traceability and individual identification. Using multiplex-PCR method with 23 MS marker divided 2 set, various alleles occurring to 5 swine breed (Berkshire, Landrace, Yorkshire, Duroc and Korea native pig) used markers to determine allele frequency and heterozygosity. MS marker found 4 alleles at SW403, S0227, SWR414, SW1041 and SW1377. The most were found 10 alleles at SW1920. Heterozygosity represented the lowest value of 0.102 at SWR414 and highest value of 0.861 at SW1920. So, it was recognized appropriate allele frequency for individual identification in swine. Using multiplex-PCR method, MS markers used to determine individual identification biomarker and breed-specific marker for faster, more accurate and lower analysis cost. Based on this result, a scientific basis was established to the existing pedigree data by applying genetics additionally. Swine traceability is expected to be very useful system and be conducted nationwide in future.

• Journal of agriculture & life science
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• v.46 no.5
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• pp.73-82
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• 2012

Allele information from the analysis of the 13 microsatellite (MS) markers, were classified into the $F_0$, $F_1$ and $F_2$ generations, and probabilities of the same individual emergency in each generation was calculated. As a result, the 13 MS markers showed an estimate of $3.84{\times}10^{-23}$ on the premise of the randomly mated group of $F_2$, which implies that the same individuals may emerge by the use of 37 kinds of SNP markers. In this study, the experimental pigs were intercross between only 2 breeds (Korean native pig and Landrace). In addition, the success rate of paternity tests was analyzed on the whole group, by the use of the 13 MS markers and 37 SNP markers. As regards the exclusionary power of the second parent ($PE_{pu}$), MS markers and SNP markers showed 0.97897 and 0.99149, respectively. In relation to the parent exclusion power of both parent (PE), MS markers and SNP markers showed 0.99916 and 0.99949, respectively. In the case of the estimate to identify parental candidates that had the highest probability ($PNE_{pp}$), the two showed 1.00000 all. The Korean pig industry tends to mass produce hogs with limited numbers of alleles in limited parents. Such being the case, there is a need to organize a marker, for which it is imperative to find markers with high efficiency and high economic feasibility of the characteristics of DNA markers, sample size, the accuracy and expenses of genotyping cost, the manageability of data and the compatibility among analysis systems.