Prediction of Genomic Relationship Matrices using Single Nucleotide Polymorphisms in Hanwoo

한우의 유전체 표지인자 활용 개체 혈연관계 추정

  • Received : 2010.04.21
  • Accepted : 2010.10.14
  • Published : 2010.10.31


The emergence of next-generation sequencing technologies has lead to application of new computational and statistical methodologies that allow incorporating genetic information from entire genomes of many individuals composing the population. For example, using single-nucleotide polymorphisms (SNP) obtained from whole genome amplification platforms such as the Ilummina BovineSNP50 chip, many researchers are actively engaged in the genetic evaluation of cattle livestock using whole genome relationship analyses. In this study, we estimated the genomic relationship matrix (GRM) and compared it with one computed using a pedigree relationship matrix (PRM) using a population of Hanwoo. This project is a preliminary study that will eventually include future work on genomic selection and prediction. Data used in this study were obtained from 187 blood samples consisting of the progeny of 20 young bulls collected after parentage testing from the Hanwoo improvement center, National Agriculture Cooperative Federation as well as 103 blood samples from the progeny of 12 proven bulls collected from farms around the Kyong-buk area in South Korea. The data set was divided into two cases for analysis. In the first case missing genotypes were included. In the second case missing genotypes were excluded. The effect of missing genotypes on the accuracy of genomic relationship estimation was investigated. Estimation of relationships using genomic information was also carried out chromosome by chromosome for whole genomic SNP markers based on the regression method using allele frequencies across loci. The average correlation coefficient and standard deviation between relationships using pedigree information and chromosomal genomic information using data which was verified using a parentage test andeliminated missing genotypes was $0.81{\pm}0.04$ and their correlation coefficient when using whole genomic information was 0.98, which was higher. Variation in relationships between non-inbred half sibs was $0.22{\pm}0.17$ on chromosomal and $0.22{\pm}0.04$ on whole genomic SNP markers. The variations were larger and unusual values were observed when non-parentage test data were included. So, relationship matrix by genomic information can be useful for genetic evaluation of animal breeding.


  1. Abdel-Azim, G. and Freeman, A. 2001. A rapid method for computing the inverse of the gametic covariance matrix between relatives for a marked quantitative trait locus. Genet. Sel. Evol. 33:153-173.
  2. Abraham, K. J., Totir, L. R. and Fernando, R. L. 2007. Improved techniques for sampling complex pedigrees with the Gibbs sampler. Genet. Sel. Evol. 39:27-38.
  3. Aguilar, I. and Misztal, I. 2008. Technical note: Recursive algorithm for inbreeding coefficients assuming nonzero inbreeding of unknown parents. J. Dairy Sci. 91:1669-1672.
  4. Arendonk, J. A. M., Tier, B. and Kinghorn, B. P. 1994. Use of multiple genetic markers in prediction of breeding values. Genetics 137:319-329.
  5. Blouin, M. S. 2003. DNA-based methods for pedigree reconstruction and kinship analysis in natural populations. TRENDS in Ecology and Evolution 18:503-511.
  6. Browning, S. R. 2008. Estimation of pairwise identity by descent from dense genetic marker data in a population sample of haplotypes. Genetics 178:2123-2132.
  7. Cannings, C. 2003. The identity by descent process along the chromosome. Human Heredity 56:126-130.
  8. Carlson, C. S., Eberle, M. A., Rieder, M. J. and Yi, Q. et al. 2004. Selecting a maximally informative set of singlenucleotide polymorphisms for association analyses using linkage disequilibrium. Am. J. Hum. Genet. 74:106-120.
  9. Chapman, N. H. and Thompson, E. A. 2003. A model for the length of tracts of identity by descent in finite random mating populations. Theor. Popul. Biology 64:141-150.
  10. Eding, H. and Meuwissen, T. H. E. 2001. Marker-based estimates of between and within population kinships for the conservation of genetic diversity. J. Anim. Breed. Genet. 118:141-159.
  11. Fernando, R. L. and Grossman, M. 1989. Marker assisted selection using best linear unbiased prediction. Genet. Sel. Evol. 21:467-477.
  12. Gengler, N., Mayeres, P. and Szydlowski, M. 2007. A simple method to approximate gene content in large pedigree populations: application to the myostatin gene in dual-purpose Belgian Blue cattle. Animal 1:21-28.
  13. Guo, S. 1996. Gametogenesis processes and multilocus gene identity by descent. Am. J. Hum. Genet. 58:408-419.
  14. Hayes, B. J. and Goddard, M. E. 2008. Technical note: Prediction of breeding values using marker-derived relationship matrices. J. Anim. Sci. 86:2089-2091.
  15. Herdenson, C. R. 1976. A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 32:69-83.
  16. Henderson, C. R. 1984. Applications of linear models in animal breeding. Can. Catal. Publ. Data. Univ. Guelph, Guelph, Ontario, Canada.
  17. Hernandez-Sanchez, J., Haley, C. S. and Woolliams, J. A. 2004. On the prediction of simultaneous inbreeding coefficients at multiple loci. Genet. Res. 83:113-120.
  18. Hernandez-Sanchez, J., Haley, C. S. and Woolliams, J. A. 2006. Prediction of IBD based on population history for fine gene mapping. Genet. Sel. Evol. 38:231-252.
  19. Hill, W. G. and Hernandez-Sanchez, J. 2007. Prediction of multilocus identity-by-descent. Genetics 176:2307-2315.
  20. Hudson, R. 1985. The sampling distribution of linkage disequilibrium under an infinite allele model without selection. Genetics 109: 611-631.
  21. Leutenegger, A. L., Prum, B., Genin, E., Verny, C., Lemainque, A., Clerget-Darpoux, F. and Thompson, E. A. 2003. Estimation of the inbreeding coefficient through use of genomic data. Am. J. Hum. Genet. 73:516-523.
  22. Libiger, O. and Schork, N. J. 2007. A simulation-based analysis of chromosome segment sharing among a group of arbitrarily related individuals. European J. of Human Genetics 15:1260-1268.
  23. Liu, Y., Jansen, G. B. and Lin, C. Y. 2002. The covariance between realtives conditional on genetic markers. Genet. Sel. Evol. 34: 657-678.
  24. Lynch, M. 1988. Estimation of relatedness by DNA fingerprinting. Mol. Biol. Evol. 5:584-599.
  25. Matsuda, H. and Iwaisaki, H. 2002. A recursive procedure to compute the gametic relationship matrix and its inverse for marked QTL clusters. Genet. Sel. Evol. 77:123-130.
  26. Meuwissen, T. H. E. and Goddard, M. E. 2000. Fine mapping of quantitative trait loci using linkage disequilibria with closely linked marker loci. Genetics 155:421-430.
  27. Meuwissen, T. H. E. and Goddard, M. E. 2001. Prediction of identity by descent probabilities from marker-haplotypes. Genet. Sel. Evol. 33:605-634.
  28. Meuwissen, T. H. E. and Goddard, M. E. 2007. Multipoint identityby-descent prediction using dense markers to map quantitative trait loci and estimate effective population size. Genetics 176:2551-2560.
  29. Nolte, I. M. and Meerman, G. J. 2002. The probability that similar haplotypes are identical by descent. Ann. Hum. Genet. 66:195-209.
  30. Perez-Enciso, M., Varona, L. and Rothschild, M. F. 2000. Computation of identity by descent probabilities conditional on DNA markers via a Monte Carlo Markov Chain method. Genet. Sel. Evol. 32:467-482.
  31. Pong-Wong, R., George, A. W., Woolliams, J. A. and Haley, C. S. 2001. A simple and rapid method for calculating identity-bydescent matrices using multiple markers. Genet. Sel. Evol. 33:453-471.
  32. Roberts, A., McMillan L., Wang, W., Parker, J., Rusyn, I. and Threadgill, D. 2007. Inferring missing genotypes in large SNP panels using fast nearest-neighbor searches over sliding windows. Bioinformatics. 23:i401-i407.
  33. Sargolzaei, M., Iwaisaki, H. and Colleau, J. J. 2006. Efficient computation of the inverse of gametic relationship matrix for a marked QTL. Genet. Sel. Evol. 38:253-264.
  34. Scheet, P. and Stephens, M. 2006. A fast and flexible statistical model for large-scale population genotype data: Applications to inferring missing genotypes and haplotypic phase. Am. J. Human Genetics. 78:629-644.
  35. Schumm, J. W., Knowlton, R. C., Braman, J. C., Baarker, D. F., Botsrein, D., Akots, G., Brown, V. A., Gravious, T. C., Helms, C., Hsiao, K., Rediker, K., Thurston, J. G. and Donis-Keller, H. 1988. Identification of more that 500 RFLPs by screening random genomic clones. Am. J. Hum. Genet. 42:143-159.
  36. Snelling, W. M, Chiu, R., Schein, J. E., Hobbs, M., Abbey, C. A., Adelson, D. L., Aerts, J., Bennett, G. L., Bosdet, I. E., Boussaha, M., Brauning R., Caetano, A. R., Costa, M. M., Crawford, A. M., Dalrymple, B. P., Eggen, A., Wind, A. E., Floriot, S., Gautier, M., Gill, C. A., Green, R. D., Holt, R., Jann, O., Jones, S., Kappes, S. M., Keele, J. W., Jong, P. J., Larkin, D. M., Lewin, H. A., McEwan, J. C., McKay, S., Marra2, M. A., Mathewson, C. A., Matukumalli, L. K., Moore, S. S., Murdoch, B., Nicholas, F. W., Osoegawa, K., Roy, A., Salih, H., Schibler, L., Schnabel, R. D., Silveri, L., Skow, L. C., Smith, T., Sonstegard, T. S., Taylor, J., Tellam, R., VanTassell, C., Williams, J. L., Womack, J. E., Wye, N. H., Yang, G. and Zhao, S. 2007. A physical map of the bovine genome. the International Bovine BAC Mapping Consortium. Genome Biology. 8:R165-1.
  37. Totir, L. R., Fernando, R. L., Dekkers, J. C. M., Fernandez, S. A. and Guldbrandtsen, B. 2004. The effect of using approximate gametic variance covariance matrices on marker assisted selection by BLUP. Genet. Sel. Evol. 36:29-48.
  38. Tuchscherer, A., Mayer, M. and Reinsch, N. 2004. Identification of gametes and treatment of linear dependencies in the gametic QTL-relationship matrix and its inverse. Genet. Sel. Evol. 36: 621-642
  39. VanRaden, P. M. 2007. Genomic measures of relationship and inbreeding. Interbull Bull. 37:33-36.
  40. VanRaden, P. M. 2008. Efficient methods to compute genomic predictions. J. Dairy Sci. 91:4414-4423.
  41. Visscher, P. M., Medland, S. E., Ferreira, M. A., Morley, K. I., Zhu, G., Cornes, B. K., Montgomery, G. W. and Martin, N. G. 2006. Assumption-free estimation of heritability from genomewide identity-by-descent sharing between full siblings. PLoS Genet. 2:e41.
  42. Wang, T., Fernando, R. L., Van Der Beek, S., Grossman, M. and Arendonk, J. A. M. 1995. Covariance between relatives for a marked quantitative trait locus. Genet. Sel. Evol. 27:251-274.
  43. Weir, B. S. and Cockerham, C. C. 1974. Behavior of pairs of loci in finite monoecious populations. Theoretical Population Biology 18:396-429.
  44. Wright, S. 1922. Coefficients of inbreeding and relationship. The American Naturalist 56:330-338 (available online at http://aipl., accessed at Aug. 20, 2009)