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Implementation of genomic selection in Hanwoo breeding program

유전체정보활용 한우개량효율 증진

Lee, Seung Hwan;Cho, Yong Min;Lee, Jun Heon;Oh, Seong Jong
이승환;조용민;이준헌;오성종

  • Received : 2015.10.19
  • Accepted : 2015.12.10
  • Published : 2015.12.31

Abstract

Quantitative traits are mostly controlled by a large number of genes. Some of these genes tend to have a large effect on quantitative traits in cattle and are known as major genes primarily located at quantitative trait loci (QTL). The genetic merit of animals can be estimated by genomic selection, which uses genome-wide SNP panels and statistical methods that capture the effects of large numbers of SNPs simultaneously. In practice, the accuracy of genomic predictions will depend on the size and structure of reference and training population, the effective population size, the density of marker and the genetic architecture of the traits such as number of loci affecting the traits and distribution of their effects. In this review, we focus on the structure of Hanwoo reference and training population in terms of accuracy of genomic prediction and we then discuss of genetic architecture of intramuscular fat(IMF) and marbling score(MS) to estimate genomic breeding value in real small size of reference population.

Keywords

Genomic selection;Genetic architecture of IMF and Hanwoo

References

  1. Barendse W, Reverter A, Bunch RJ, Harrison BE, Barris W, Thomas MB. 2007. A Validated Whole-Genome Association Study of Efficient Food Conversion in Cattle. Genetics. 176:1893-1905. https://doi.org/10.1534/genetics.107.072637
  2. Calus MPL. 2010. Genomic breeding value prediction: methods and procedures. Animal. 4:157-164. https://doi.org/10.1017/S1751731109991352
  3. Daetwyler HD, Schenkel FS, Sargolzaei M, Robinson JAB. 2008. A genome scan to detect quantitative trait loci for economically important traits in Holstein cattle using two methods and a dense single nucleotide polymorphism map. Journal of Dairy Science. 91:3225-3236. https://doi.org/10.3168/jds.2007-0333
  4. de Roos APW, Schrooten C, Mullaart E, Cander BS, de Jong G, Voskamp W. 2009. Genomic selection at CRV. Interbull international workshop, Uppsala, Sweden, January 26-29. Interbull Bulletin 39:47-50.
  5. Dekker JCM, Hospital F. 2002. The use of molecular genetics in the improvement of agricultural populations. Nature Review Genetics 3:22-32. https://doi.org/10.1038/nrg701
  6. Durr J, Philipsson J. 2011. International cooperation: The pathway for cattle genomics. Animal Frontiers. doi:10.2527/af.2011-0026.
  7. Eggen A. 2011. The development and application of genomic selection as a new breeding paradigm. Animal Frontiers. doi:10.2527/af.2011-0027.
  8. Fernando RL, Grossman M. 1989. Marker assisted selection using best linear unbiased prediction. Genetic Selection Evolution. 21:467-477. https://doi.org/10.1186/1297-9686-21-4-467
  9. George M, Nielsen D, Mackinnon M, Mishra A, Okimoto R, Pasquino AT, Sargeant LS, Sorensen A, Steele MR, Zhao X, Womack JE, Hoeschele I. 1995. Mapping Quantitative Trait Loci Controlling Milk Production in Dairy Cattle by Exploiting Progeny Testing. Genetics. 139(2):907-920.
  10. Goddard ME, Hayes BJ, Meuwissen THE. 2010. Genomic selection in livestock populations. Genetic Research. (Camb.) 92:413-421. https://doi.org/10.1017/S0016672310000613
  11. Goddard ME, Hayes BJ. 2009. Mapping genes for complex traits in domestic animals and their use in breeding programs. Nature Review Genetics.10:381-391. https://doi.org/10.1038/nrg2575
  12. Grapes L, Dekkers JC, Rothschild MF, Fernando RL. 2004. Comparing linkage disequilibrium-based methods for fine mapping quantitative trait loci. Genetics. 166:1561-1570. https://doi.org/10.1534/genetics.166.3.1561
  13. Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME. 2009. Invited review: Genomic selection in dairy cattle: Progress and challenges. Journal of Dairy Science. 92:433-443. https://doi.org/10.3168/jds.2008-1646
  14. Heffner E, Sorrells M, Jannink J. 2009. Genomic selection for crop improvement. Crop Science. 49:1-12. https://doi.org/10.2135/cropsci2008.08.0512
  15. Hu Z, Fritz ER, Reecy J M. 2007. AnimalQTLdb: A Livestock QTL Database Tool Set for Positional QTL Information Mining and Beyond. Nucleic Acids Research. 35:D604-D609. https://doi.org/10.1093/nar/gkl946
  16. Kolbehdari D, Wang Z, Grant JR, Murdoch B, Prasad A, Xiu Z, Marques E, Stothard P, Moore SS. 2008. A whole genome scan to map quantitative trait loci for conformation and functional traits in Canadian Holstein Bulls. Journal of Dairy Science. 91:2844-2856. https://doi.org/10.3168/jds.2007-0585
  17. Aulchenko YS, de Koning DJ, Haley, C. 2007. Genomewide rapid association using mixed model and regression: A fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics. 177:577-585 https://doi.org/10.1534/genetics.107.075614
  18. Lee SH, Cho YM, Lim D, Kim HC, Choi BH, Park HS, Kim OH, Kim S, Kim TH, Yoon D, Hong SK. 2011 Linkage Disequilibrium and Effective Population Size in Hanwoo Korean Cattle. AJAS 24:1660-1665.
  19. Lee SH. 2011. Genome analyses to identify genes and QTL affecting carcass traits in Hanwoo. PhD Thesis, University of New England, Armidale, Australia.
  20. Meuwissen THE, Hayes BJ, Goddard ME. 2001. Prediction of Total Genetic Value Using Genome-Wide Dense Marker Maps Genetics. 157:1819-1829.
  21. Muller M, Kersten S. 2003 Nutrigenomics: goals and strategies. Nature Review Genetics. 4:315-322. https://doi.org/10.1038/nrg1047
  22. Park B, Choi T, Kim S, Oh SH. National genetic evaluation (system) of Hanwoo (Korean native cattle). Asian-Australas J. Anim. Sci. 26(2):151-156. https://doi.org/10.5713/ajas.2012.12439
  23. Pszczola M, Strabel T, Mulder HA, Calus MPL. 2012. Reliability of direct genomic values for animals with different relationships within and to the reference population. Journal of Dairy Science. 95:389-400. https://doi.org/10.3168/jds.2011-4338
  24. VanRaden PM. 2008. Efficient methods to compute genomic predictions. Journal of Dairy Science. 91:4414-4423. https://doi.org/10.3168/jds.2007-0980

Cited by

  1. Accuracy of Genomic Estimated Breeding Value with Hanwoo Cows in the Commercial Farms vol.52, pp.2, 2018, https://doi.org/10.14397/jals.2018.52.2.91

Acknowledgement

Supported by : 제주대학교