DOI QR코드

DOI QR Code

Molecular genetic evaluation of gorals(naemorhedus caudatus raddeanus) genetic resources using microsatellite markers

초위성체 마커를 이용한 산양의 분자유전학적 고찰

  • Seo, Joo Hee (The Graduate School of Future Convergence Technology, Department of Genomic Informatics, Hankyong National University) ;
  • Lee, Yoonseok (Genomic Informatics Center, Hankyong National University) ;
  • Jeon, Gwang Joo (Genomic Informatics Center, Hankyong National University) ;
  • Kong, Hong Sik (Genomic Informatics Center, Hankyong National University)
  • 서주희 (한경대학교 미래융합기술대학원 유전체정보전공) ;
  • 이윤석 (한경대학교 유전정보연구소) ;
  • 전광주 (한경대학교 유전정보연구소) ;
  • 공홍식 (한경대학교 유전정보연구소)
  • Received : 2017.05.10
  • Accepted : 2017.09.07
  • Published : 2017.09.30

Abstract

In this study, genotyping was executed by using 13 microsatellite markers for genetic diversity of 224 Gorals (Saanen(88), Laoshan(67), Toggenburg(32), Alpine(12), Anglonubian(9), Jamnapari(7) and Black Bengal(4)). The number of alleles was observed 4 (INRA005) to 18 (SRCRSP23) each markers. Observed heterozygostiy ($H_{obs}$), expected heterozygosity ($H_{\exp}$) and polymorphism information content (PIC) were observed 0.482 to 0.786, 0.476 to 0.923, and 0.392 to 0.915, respectively. Principal Components Analysis(PCoA) results were similar to the results of FCA. NE-I(on-exclusion probability for identity of two unrelated individuals) was estimated at $2.47{\times}10^{-15}$. In conclusion, this study shows the useful data that be utilized as a basic data of Gorals breeding and development.

본 연구는 산양 7 품종을 대상으로 (Saanen (88), Laoshan (67), Toggenburg (32), Alpine (12), Anglonubian (9), Jamnapari (7), Black Bengal (4)) 13종의 초위성체 마커 (microsatellite marker)를 활용하여 유전적 다형성 분석을 실시하였다. 대립유전자 수는 4개 (INRA005) 부터 18개 (SRCRSP23)까지 확인되었으며, 관측이형접합율 ($H_{obs}$)과 기대이형접합율 ($H_{\exp}$) 그리고 다형성 정보지수 (PIC) 값은 각각 0.482 ~ 0.786, 0.476 ~ 0.923 그리고 0.392 ~ 0.915로 나타났다. 품종별 유전적 거리를 확인하기 위하여 실시한 주성분분석 (PCoA) 결과는 요인대응분석 (FCA) 분석과 유사한 결과를 보였으며, 동일개체출현빈도는 $2.47{\times}10^{-15}$으로 확인되었다. 따라서 본 연구 결과는 산양 품종 개량 및 보존에 있어 기초자료로써 유용한 자료로 활용 가능 할 것으로 사료된다.

Keywords

References

  1. Albenzio, M. and Santillo, A. (2011). Biochemical characteristics of ewe and goat milk: Effect on the quality of dairy products. Small Ruminant Research, 101, 33-40. https://doi.org/10.1016/j.smallrumres.2011.09.023
  2. Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N. and Bonhomme, F. (1996-2004). GENETIX 4.05, logiciel sous windows TM pour la genetique des populations, Laboratoire Genome, Populations, Interactions, CNRS UMR 5171, Universite de Montpellier II, Montpellier. France.
  3. Blott, S. C., Williams, J. L. and Haley, C. S. (1999). Discriminating among cattle breeds using genetic markers. Heredity, 82, 613-619. https://doi.org/10.1046/j.1365-2540.1999.00521.x
  4. Faostat, F. (2012). Disponivel em: http://faostat.fao.org, Acesso em, 14.
  5. Ciampolini, R., Moazami-Goudarzi, K., Vaiman, D., Dillmann, C., Mazzanti, E. and Foulley, J. L. (1995). Individual multilocus genotypes using microsatellite polymorphisms to permit the analysis of the genetic variability within and between Italian beef cattle breeds. Journal of Animal Science, 73, 3259-3268. https://doi.org/10.2527/1995.73113259x
  6. Haenlein, G. (2004). Goat milk in human nutrition. Small Ruminant Research, 51, 55-163.
  7. Jung, T. H., Hwang, H. J., Yun, S. S., Lee, W. J., Kim, J. W., Shin, K. O., and Han, K. S. (2016). The Commercial Value of Goat Milk in Food Industry. Journal of Milk Science and Biotechnology, 34, 173-180. https://doi.org/10.22424/jmsb.2016.34.3.173
  8. Kim, H. H., Park, Y. S. and Yoon, S. S. (2014). Major Components of Caprine Milk and Its Significance for Human Nutrition. Korean Journal of Food Science and Technology, 46, 121-126. https://doi.org/10.9721/KJFST.2014.46.2.121
  9. Lee, J. Y., Bae, J. H. and Yeo, J. S. (2007). Bootstrapping and DNA marker Mining of BMS941 microsatellite Locus in Hanwoo chromosome 17. Journal of the Korean Data & Information Science Society, 18, 1103-1113.
  10. Loftus, R. T., Ertugrul, O., Harba, A. H., El-Barody, M. A. A., MacHugh, D. E., Park, S. D. E. and Bradley, D. G. (1999). A microsatellite survey of cattle from a centre of origin: The Near East. Molecular Ecology, 8, 2015-2022. https://doi.org/10.1046/j.1365-294x.1999.00805.x
  11. Marshall, T., Slate, C. J., Kruuk, L. E. and Pemberton, J. M. (1998). Statistical confidence for likelihoodbased paternity inference in natural populations. Molecular Ecology, 7, 639-655. https://doi.org/10.1046/j.1365-294x.1998.00374.x
  12. Martin-Burriel, I., Garcia-Muro, E. and Zaragoza, P. (1999). Genetic diversity analysis of six Spanish native cattle breeds using microsatellites. Animal Genetics, 30, 177-182. https://doi.org/10.1046/j.1365-2052.1999.00437.x
  13. Moazami-Goudarzi, K, Laloe, D., Furet, J. P. and Grosclaude, F. (1997). Analysis of genetic relationships between 10 cattle breeds with 17 microsatellites. Animal Genetics, 28, 338-345. https://doi.org/10.1111/j.1365-2052.1997.00176.x
  14. Park, S. D. E. (2001). Trypanotolerance in West African cattle and the population genetic effects of selection, Ph.D. Thesis, University of Dublin.
  15. Peelman, L. J., Mortiaux, F., Van Zeveren, A., Dansercoer, A., Mommens, G., Coopman, F., Bouquet, Y., Burny, A., Renaville, R. and Portetelle, D. (1998). Evaluation of the genetic variability of 23 bovine microsatellite markers in four Belgian cattle breeds. Animal Genetics, 29, 161-167. https://doi.org/10.1111/j.1365-2052.1998.00280.x
  16. Raynal-Ljutovac, K., Gaborit, P. and Lauret, A. (2005). The relationship between quality criteria of goat milk, its technological properties and the quality of the final products. Small Ruminant Research, 60, 167-177. https://doi.org/10.1016/j.smallrumres.2005.06.010
  17. Ruane, J. (1999). A critical review of the value of genetic distance studies in conservation of animal gentic resources. Journal of Animal Breeding and Genetics, 116, 317-323. https://doi.org/10.1046/j.1439-0388.1999.00205.x
  18. Schmid, M., Saitbekova, N., Gaillard, C. and Dolf. G. (1999). Genetic diversity in Swiss cattle breeds. Journal of Animal Breeding and Genetics, 116, 1-8. https://doi.org/10.1111/j.1439-0388.1999.00165.x
  19. Talpur, F. N., Bhanger, M. and Memon, N. N. (2009). Milk fatty acid composition of indigenous goat and ewe breeds from Sindh. Pakistan Journal of Food Composition and Analysis , 22, 59-64. https://doi.org/10.1016/j.jfca.2008.09.005
  20. Weir, B. S. and Cockerham, C. C. (1984). Estimating F-statistics for the analysis of population structure. Evolution, 38, 358-1370.
  21. Wright, S. (1951). The genetical structure of populaitons. Annals of Eugenics, 15, 323-354.
  22. Yangilar, F. (2013). As a potentially functional food: goats'milk and products. Journal of Food and Nutrition Research, 1, 68-81.
  23. Zheng, S., Lee, J. H., Lee, Y. S., Oh, D. Y. and Yeo, J. S. (2010). Analysis of genetic diversity and distances in Asian cattle breeds using microsatellite markers. Journal of the Korean Data & Information Science Society, 21, 798-802.