Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Evaluation of Inbreeding and Genetic Variability of Five Pig Breeds in Czech Republic

  • Krupa, Emil (Institute of Animal Science) ;
  • Zakova, E. (Institute of Animal Science) ;
  • Krupova, Z. (Institute of Animal Science)
  • Received : 2014.04.04
  • Accepted : 2014.08.04
  • Published : 2015.01.01
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Abstract

The complex analysis of the pedigree records of Czech Landrace (CLA), Czech Large White-dam line (CLWd), Czech Large White-sire line (CLWs), Duroc (DC), and Pietrain (PN) was performed to determine trends of genetic diversity (GD), and to find the main sources of the GD loss. The total size of the pedigree was 132,365, 391,151, 32,913, 13,299, and 7,160 animals in CLA, CLWd, CLWs, DC, and PN, respectively. Animals born in the years 2011 through 2013 were assumed as the reference population. The average pedigree completeness index for one generation back was 95.9%, 97.4%, 91.2%, 89.8%, and 94.2% for appropriate breeds. Number of ancestors explaining 100% of gene pool was 186, 373, 125, 157, and 37 in CLA, CLWd, CLWs, DC, and PN, respectively. The relative proportion of inbred animals (58%, 58%, 54%, 47%, and 25%), the average inbreeding (2.7%, 1.4%, 2.5%, 3.6%, and 1.3%) and the average co-ancestry (3.1%, 1.6%, 3.3%, 4.2%, and 3.3%) were found over the past decade in analysed breeds. The expected inbreeding under random mating increased during the last 10 years in CLWs and PN and varied from 1.27% to 3.2%. The effective population size computed on the basis of inbreeding was 76, 74, 50, 35, and 83 in 2012 in CLA, CLWd, CLWs, DC, and PN, respectively. The shortest generation interval (1.45) was observed for CLWd in sire to son selection pathway. The longest generation interval obtained PN (1.95) in sire to daughter pathway. The average relative GD loss within last generation interval was 7.05%, 4.70%, 9.81%, 7.47%, and 10.46%, respectively. The relative proportion of GD loss due to genetic drift on total GD loss was 85.04%, 84.51%, 89.46%, 86.19%, and 83.68% in CLA, CLWd, CLWs, DC, and PN, respectively. All breeds were characterized by a high proportion of inbred animals, but the average inbreeding was low. The most vulnerable breeds to loss of GD are DC and PN. Therefore, a breeding program should be more oriented to prevent the increase of GD loss in these breeds.

Keywords

References

  1. Berg, P. 2012. EVA version 1.75. Evolutionary algorithm for mate selection. User's Guide. Institute of Arhus, Institute of Genetic and Biotechnology, Tjele, Denmark.
  2. Bijma, P. and J. A. Woolliams. 1999. Prediction of genetic contributions and generation intervals in populations with overlapping generations under selection. Genetics 151:1197-1210.
  3. Boichard, D., L. Maignel, and E. Verrier 1997. The value of using probabilities of gene origin to measure genetic variability in a population. Genet. Sel. Evol. 29:5-23. https://doi.org/10.1186/1297-9686-29-1-5
  4. Boichard, D. 2002. PEDIG: a fortran package for pedigree analysis suited for large populations. In: Proc. of the 7th World Congress on Genetics Applied to Livestock Production (WCGALP). INRA, Castanet-Tolosan, France [CD-Rom]. pp. 19-23.
  5. Caballero, A. and M. A. Toro 2000. Interrelations between effective population size and other tools for management of conserved populations. Genet. Res. 75:331-343. https://doi.org/10.1017/S0016672399004449
  6. Colleau, J. J. 2002. An indirect approach to the extensive calculation of relationship coefficients. Genet. Sel. Evol. 34:409-421. https://doi.org/10.1186/1297-9686-34-4-409
  7. Falconer, D. S. and T. F. C. Mackay 1996. Introduction to Quantitative Genetics. 4th Ed. Longman Scientific and Technical, Harlow, UK.
  8. FAO 2000. Secondary guidelines for development of farm animal genetic resources management plans. Management of small populations at risk. FAO, Rome, Italy.
  9. Fernandez, J., B. Villanueva, R. Pong-Wong, and M. A. Toro 2005. Efficiency of the use of pedigree and molecular marker information in conservation programs. Genetics 170:1313-1321. https://doi.org/10.1534/genetics.104.037325
  10. Groeneveld, E., B. Van der Westhuizen, A. Maiwashe, F. Voordewind, and J. B. S. Ferraz. 2009. POPREP: A generic report for population management. Genet. Mol. Res. 8:1158-1178. https://doi.org/10.4238/vol8-3gmr648
  11. Honda, T., T. Nomura, Y. Yamaguchi, and F. Mukai 2004. Monitoring of genetic diversity in the Japanese Black cattle population by the use of pedigree information. J. Anim. Breed. Genet. 121:242-252. https://doi.org/10.1111/j.1439-0388.2004.00452.x
  12. Koenig, S. and H. Simianer 2006. Approaches to the management of inbreeding and relationship in the German Holstein dairy cattle population. Livest. Sci. 103:40-53. https://doi.org/10.1016/j.livsci.2005.12.009
  13. Lacy, R. C. 1995. Classification of genetic terms and their use in the management of captive populations. Zoo Biol. 14:565-577. https://doi.org/10.1002/zoo.1430140609
  14. MacCluer, J. W., A. J. Boyce, B. Dyke, L. R. Weitkamp, D. W. Pfennig, and C. J. Parsons 1983. Inbreeding and pedigree structure in Standardbred horses. J. Hered. 74:394-399.
  15. Maignel, L., D. Boichard, and E. Verrier 1996. Genetic variability of French dairy breeds estimated from pedigree information. Interbull Bulletin 14:49-54.
  16. Melka, M. G. and F. Schenkel. 2010. Analysis of genetic diversity in four Canadian swine breeds using pedigree data. Can. J. Anim. Sci. 90:331-340. https://doi.org/10.4141/CJAS10002
  17. Meuwissen, T. H. E. and Z. Luo 1992. Computing in breeding coefficients in large populations. Genet. Sel. Evol. 24:305-313. https://doi.org/10.1186/1297-9686-24-4-305
  18. Meuwissen, T. H. E. and J. A. Woolliams 1994. Effective sizes of livestock populations to prevent a decline in fitness. Theor. Appl. Genet. 89:1019-1026.
  19. Nei, M. 1973. Analysis of gene diversity in subdivided populations. Prod. Natl. Acad. Sci. 70:3321-3323. https://doi.org/10.1073/pnas.70.12.3321
  20. Nicholas, F. W. 1989. Incorporation of new reproductive technology in genetic improvement programmes. In: Evolution and Animal Breeding (Eds. W. G. Hill and T. F. C. Mackay). CAB Int., Wallingford, UK. pp. 201-209.
  21. Norberg, E. and A. C. Sorensen 2007. Inbreeding trend and inbreeding depression in the Danish populations of Texel, Shropshire, and Oxford Down. J. Anim. Sci. 85:299-304. https://doi.org/10.2527/jas.2006-257
  22. Oravcova, M. 2013. Pedigree analysis in White Shorthaired goat: First results. Arch. Tierz. 56:547-554.
  23. Pjontek, J., O. Kadlecik, R. Kasarda, and M. Horny. 2012. Pedigree analysis in four Slovak endangered horse breeds. Czech J. Anim. Sci. 57:54-64.
  24. Sargolzaei, M., H. Iwaisaki, and J. J. Colleau. 2006. CFC: A tool for monitoring genetic diversity. In: Proc. of the 8th World Congress on Genetics Applied to Livestock Production(WCGALP). August 13-18, 2006. Belo Horizonte, Brazil. pp. 27-28
  25. Sorensen, A. C., M. K. Sørensen, and P. Berg. 2005. Inbreeding in Danish dairy cattle breeds. J. Dairy Sci. 88:1865-1872. https://doi.org/10.3168/jds.S0022-0302(05)72861-7
  26. Tang, G. Q., J. Xue, M. J. Lian, R. F. Yang, T. F. Liu, Z. Y. Zeng, A. A. Jiang, Y. Z. Jiang, L. Zhu, L. Bai, Z. Wang, and X. W. Li 2013. Inbreeding and genetic diversity in three imported swine breeds in china using pedigree data. Asian Australas. J. Anim. Sci. 26:755-765. https://doi.org/10.5713/ajas.2012.12645
  27. Uimari, P. and M. Tapio. 2011. Extent of linkage disequilibrium and effective population size in Finish Landrace and Finish Yorkshire pig breeds. J. Anim. Sci. 89:609-614. https://doi.org/10.2527/jas.2010-3249
  28. Welsh, C. S., T. S. Stewart, C. Schwab, and H. D. Blackburn. 2010. Pedigree analysis of 5 swine breeds in the United States and the implications for genetic conservation. J. Anim. Sci. 88:1610-1618. https://doi.org/10.2527/jas.2009-2537

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