Simulation Study on Parentage Analysis with SNPs in the Japanese Black Cattle Population

  • Received : 2008.12.08
  • Accepted : 2008.05.18
  • Published : 2009.10.01


Parentage tests using polymorphic DNA marker are commonly performed to avoid incorrect recording of the parental information of livestock animals, and single-nucleotide polymorphisms (SNPs) are becoming the method of choice. In Japanese Black cattle, parentage tests based on the exclusion method using microsatellite markers are currently conducted; however, an alternative SNP system aimed at parentage tests has recently been developed. In the present study, two types of simulations were conducted using the pedigree data of two subpopulations in the breed (subpopulations of Hyogo and Shimane prefectures) in order to examine the effect of actual genetic and breeding structures. The first simulation (simulation 1) investigated the usefulness of SNPs for excluding a close relative of the true sire; the second one (simulation 2) investigated the accuracy of sire identification tests for multiple full-sib putative sires by a combined method of exclusion and paternity assignment based on the LOD score. The success rates of excluding a single fullsib and sire of the true sires were, respectively, 0.9915 and 0.9852 in Hyogo and 0.9848 and 0.9852 in Shimane, when 50 SNPs with minor allele frequency (MAF: q) of 0.25${\leq}$q${\leq}$0.35 were used in simulation 1. The success rates of sire identification tests based solely on the exclusion method were relatively low in simulation 2. However, assuming that 50 SNPs with MAF of 0.25${\leq}$q${\leq}$0.35 or 0.45${\leq}$q${\leq}$0.5 were available, the total success rates including achievements due to paternity assignment were, respectively, 0.9430 and 0.9681 in Hyogo and 0.8999 and 0.9399 for Shimane, even when each true sire was assumed to compete with 50 full-sibs.


  1. Double, M. C., A. Cockburn, S. C. Barry and P. E. Smouse. 1997, Exclusion probabilities for single-locus paternity analysis when related males compete for matings, Mol. Ecol. 6:1155-1166
  2. Gomez-Raya, L., K. Priest, W. M. Rauw, M. Okomo-Adhiambo, D. Thain, B. Bruce, A. Rink, R. Torell, L. Grellman, R. Narayanan and C. W. Beattie. 2008, The value of DNA paternity identification in beef cattle: Examples from Nevada's free-range ranches, J. Anim. Sci. 86:17-24
  3. Heaton, M. P., G. P. Harhay, G. L. Bennett, R. T. Stone, W. M. Grosse, E. Casas, J. W. Keele, T. P. L. Smith, C. G. Chitko- McKown and W. W. Laegreid. 2002, Selection and use of SNP markers for animal identification and paternity analysis in US beef cattle. Mamm, Genome 13:272-281
  4. Honda, T., T. Nomura, Y. Yamaguchi and F. Mukai. 2002, Pedigree analysis of genetic subdivision in a population of Japanese Black cattle, Anim. Sci. J. 73:445-452
  5. Marshall, T. C., J. Slate, L. E. B. Kruuk and J. M. Pemberton. 1998, Statistical confidence for likelihood-based paternity inference in natural populations, Mol. Ecol 7:639-655
  6. Rohrer, G. A., B. A. Freking and D. Nonneman. 2007, Single nucleotide polymorphisms for pig identification and parentage exclusion, Anim. Genet. 38:253-258
  7. Dodds, K. G., M. L. Tate and J. A. Sise. 2005, Genetic evaluation using parentage information from genetic markers, J. Anim. Sci. 83:2271-2279
  8. Meagher, T. R. 1986, Analysis of paternity within a natural population of Chamaelirium luteum. I. Identification of mostlikely male parents, Am. Nat. 128:199-215
  9. Robertson, A. 1965, The interpretation of genotypic ratios in domestic animal populations, Anim. Prod. 7:319-324
  10. Baruch, E. and J. I. Weller. 2008, Estimation of the number of SNP genetic markers required for parentage verification, Anim. Genet. 39:474-479
  11. Nei, M. 1977, F-statistics and analysis of gene diversity in subdivided populations, Ann. Hum. Genet. 41:225-233
  12. Caballero, A. and M. A. Toro. 2000, Interrelations between effective population size and other pedigree tools for management of conserved populations, Genet. Res. Camb. 75:331-343
  13. MacCluer, J. W., J. L. VandeBerg, B. Read and O. A. Ryder. 1986, Pedigree analysis by computer simulation, Zoo. Biol. 5:147-160
  14. Chakraborty, R., T. R. Meagher and P. E. Smouse. 1988, Parentage analysis with genetic markers in natural populations. I. The expected proportion of offspring with unambiguous paternity, Genetics 118:527-536
  15. Frankham, R., J. D. Ballou and D. A. Briscoe. 2002. Introduction to Conservation Genetics. Cambridge University Press, Cambridge
  16. Hill, W. G., B. A. Salisbury and A. J. Webb. 2008, Parentage identification using single nucleotide polymorphism genotypes: Application to product tracing, J. Anim. Sci. 86:2508-2517
  17. Kalinowski, S. T., M. L. Taper and T. C. Marshall. 2007, Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment, Mol. Ecol. 16:1099-1106
  18. Werner, F. A. O., G. Durstewitz, F. A. Habermann, G. Thaller, W. Kr$\ddot{a}$mer, S. Kollers, J. Buitkamp, M. Georges, G. Brem, J. Mosner and R. Fries. 2004, Detection and characterization of SNPs useful for identity control and parentage testing in major European dairy breeds, Anim. Genet. 35:44-49
  19. Anderson, E. C. and J. C. Garza. 2006, The power of singlenucleotide polymorphisms for large-scale parentage inference, Genetics 172:2567-2582
  20. Wang, J. 1996, Deviation from Hardy-Weinberg proportions in finite populations, Genet. Res., Camb. 68:249-257
  21. Eenennaam, A. L. V., R. L. Weaber, D. J. Drake, M. C. T. Penedo, R. L. Quaas, D. J. Garrick and E. J. Pollak. 2007, DNA-based paternity analysis and genetic evaluation in a large, commercial cattle ranch setting, J. Anim. Sci. 85:3159-3169
  22. Dodds, K. G., M. L. Tate, J. C. McEwan and A. M. Crawford. 1996, Exclusion probabilities for pedigree testing farm animals, Theor. Appl. Genet. 92:966-975
  23. Jones, A. and W. R. Ardren. 2003, Methods of parentage analysis in natural populations, Mol. Ecol. 12:2511-2523

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