DOI QR코드

DOI QR Code

한우의 유전체 표지인자 활용 개체 혈연관계 추정

Prediction of Genomic Relationship Matrices using Single Nucleotide Polymorphisms in Hanwoo

  • 투고 : 2010.04.21
  • 심사 : 2010.10.14
  • 발행 : 2010.10.31

초록

한우의 유전체 전장의 정보를 Illumina BeadArray$^{TM}$ Bovine SNP50 assay를 이용하여 단일염기다형 현상을 조사한 결과, 유전적 다양성을 보이는 좌위가 약 32,567 좌위 이상에서 다양성을 보이고 있었으며 약 5,554 좌위에서 다양성이 조사되지 않았다. 이는 조사된 자료의 가계집단의 수가 크게 제한되었기 때문에 기인될 수 있으며 또 다른 원인으로는 한우 종축집단의 크기가 작을 수 있다는 현상을 반증한다고 사료된다. 유전분석의 기초가 되는 혈통기록에 의한 개체간 혈연관계를 유전체 정보에 의한 혈연관계와 비교하여 본 결과, 유전체 정보에 의한 혈연관계의 크기가 혈통기록에 의한 혈연관계보다 좀 더 정확하게 추정될 수 있다는 장점이 있으며 혈통기록상의 오류로 그릇된 혈연관계의 크기를 유전체 정보를 통하여 보완할 수 있다는 장점이 있다. 이러한 장점을 활용하면 유전체정보를 이용한 유전능력 평가의 정확성을 크게 향상시킬 수 있을 것으로 사료되었다.

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.

키워드

참고문헌

  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. https://doi.org/10.1186/1297-9686-33-2-153
  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. https://doi.org/10.1186/1297-9686-39-1-27
  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. https://doi.org/10.3168/jds.2007-0575
  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. https://doi.org/10.1016/S0169-5347(03)00225-8
  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. https://doi.org/10.1534/genetics.107.084624
  7. Cannings, C. 2003. The identity by descent process along the chromosome. Human Heredity 56:126-130. https://doi.org/10.1159/000073740
  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. https://doi.org/10.1086/381000
  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. https://doi.org/10.1016/S0040-5809(03)00071-6
  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. https://doi.org/10.1046/j.1439-0388.2001.00290.x
  11. Fernando, R. L. and Grossman, M. 1989. Marker assisted selection using best linear unbiased prediction. Genet. Sel. Evol. 21:467-477. https://doi.org/10.1186/1297-9686-21-4-467
  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. https://doi.org/10.1017/S1751731107392628
  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. https://doi.org/10.2527/jas.2007-0733
  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. https://doi.org/10.2307/2529339
  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. https://doi.org/10.1017/S0016672303006633
  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. https://doi.org/10.1186/1297-9686-38-3-231
  19. Hill, W. G. and Hernandez-Sanchez, J. 2007. Prediction of multilocus identity-by-descent. Genetics 176:2307-2315. https://doi.org/10.1534/genetics.107.074344
  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. https://doi.org/10.1086/378207
  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. https://doi.org/10.1038/sj.ejhg.5201910
  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. https://doi.org/10.1186/1297-9686-34-6-657
  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. https://doi.org/10.1186/1297-9686-33-6-605
  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. https://doi.org/10.1534/genetics.107.070953
  29. Nolte, I. M. and Meerman, G. J. 2002. The probability that similar haplotypes are identical by descent. Ann. Hum. Genet. 66:195-209. https://doi.org/10.1046/j.1469-1809.2002.00110.x
  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. https://doi.org/10.1186/1297-9686-32-5-467
  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. https://doi.org/10.1186/1297-9686-33-5-453
  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. https://doi.org/10.1093/bioinformatics/btm220
  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. https://doi.org/10.1186/1297-9686-38-3-253
  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. https://doi.org/10.1086/502802
  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. https://doi.org/10.1186/gb-2007-8-8-r165
  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. https://doi.org/10.1186/1297-9686-36-1-29
  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 https://doi.org/10.1186/1297-9686-36-6-621
  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. https://doi.org/10.3168/jds.2007-0980
  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. https://doi.org/10.1371/journal.pgen.0020041
  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. https://doi.org/10.1186/1297-9686-27-3-251
  43. Weir, B. S. and Cockerham, C. C. 1974. Behavior of pairs of loci in finite monoecious populations. Theoretical Population Biology 18:396-429. https://doi.org/10.1016/0040-5809(80)90061-1
  44. Wright, S. 1922. Coefficients of inbreeding and relationship. The American Naturalist 56:330-338 (available online at http://aipl. arsusda.gov/publish/other/wright1922.pdf, accessed at Aug. 20, 2009) https://doi.org/10.1086/279872