DOI QR코드

DOI QR Code

What Holds the Future of Quantitative Genetics? - A Review

  • Lee, Chaeyoung (Laboratory of Statistical Genetics, Institute of Environment and Life Science, Hallym University)
  • Published : 2002.02.01

Abstract

Genetic markers engendered by genome projects drew enormous interest in quantitative genetics, but knowledge on genetic architecture of complex traits is limited. Complexities in genetics will not allow us to easily clarify relationship between genotypes and phenotypes for quantitative traits. Quantitative genetics guides an important way in facing such challenges. It is our exciting task to find genes that affect complex traits. In this paper, landmark research and future prospects are discussed on genetic parameter estimation and quantitative trait locus (QTL) mapping as major subjects of interest.

Keywords

References

  1. Breslow, N. E. and D. G. Clayton. 1993. Approximate inference in generalized linear mixed models. J. Am. Stat. Assoc. 88:9-25. https://doi.org/10.2307/2290687
  2. Casella, G. and R. L. Berger. 1990. Statistical Inference. Wadsworth and Brooks/Cole, Pacific Grove, CA.
  3. Crow, J. F. and M. Kimura. 1970. An Introduction to Population Genetics Theory. Harper & Row, New York, NY, USA.
  4. Fisher, R. A. 1925. Statistical methods for research workers. Oliver and Boyd, Edinburgh, England.
  5. Fisher, R. A. 1930. The genetic thoery of natural selection. Dover, New York, NY, USA.
  6. George, A. W., P. M. Visscher and C. S. Haley. 2000. Mapping quantitative trait loci in complex pedigrees: a two-step variance component approach. Genetics 156:2081-2092.
  7. Gianola, D. and R. L. Fernando. 1986. Bayesian methods in animal breeding theory. J. Anim. Sci. 63:217-244. https://doi.org/10.2527/jas1986.631217x
  8. Hartley, H. O. and J. N. K. Rao. 1967. Maximum-likelihood estimation for the mixed analysis of variance model. Biomtrika 54:93-108. https://doi.org/10.1093/biomet/54.1-2.93
  9. Henderson, C. R. 1953. Estimation of variance and covariance components. Biometrics 9:226-252. https://doi.org/10.2307/3001853
  10. Jensen, J. and I. L. Mao. 1991. Estimation of genetic parameters using sampled data from population undergoing selection. J. Dairy Sci. 74:3544-3551. https://doi.org/10.3168/jds.S0022-0302(91)78546-9
  11. Jensen, J., C. S. Wang, D. A. Sorenson and D. Gianola. 1994. Bayesian inference on variance and covariance components for traits influenced by maternal and direct genetic effects, using the Gibbs sampler. Acta Agric. Scand. 44:193-201.
  12. Kao, C. H., Z. B. Zeng and R. D. Teasdale. 1999. Multiple interval mapping for quantitative trait loci. 152:1203-1216.
  13. Lander, E. S. and D. Botstein. 1989. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185-199.
  14. Lee, C. 2000a. Methods and techniques for variance component estimation in animal breeding. Asian-Aus. J. Anim. Sci. 13:413-422.
  15. Lee, C. 2000b. Likelihood-based inference on genetic variance component with a hierarchical Poisson generalized linear mixed model. Asian-Aus. J. Anim. Sci. 13:1035-1039. https://doi.org/10.5713/ajas.2000.1035
  16. Lee, C and Y. Lee. 1998. Sire evaluation of count traits with a Poisson-gamma hierarchical generalized linear model. Asian-Aus. J. Anim. Sci. 11:642-647. https://doi.org/10.5713/ajas.1998.642
  17. Lee, C. and E. J. Pollak. 1997a. Influence of sire misidentification on sire ${\times}$ year interaction variance and direct-maternal genetic covariance for weaning weight in beef cattle. J. Anim. Sci. 75:2858-2863.
  18. Lee, C. and E. J. Pollak. 1997b. Relationship between sire x year interactions and direct-maternal genetic correlation for weaning weight of Simmental cattle. J. Anim. Sci. 75:68-75. https://doi.org/10.2527/1997.75168x
  19. Lee, C. and E. J. Pollak. 2001. Genetic antagonism between body weight and milk production in beef cattle. J. Anim. Sci. (In press)
  20. Lynch, M. and B. Walsh. 1998. Genetics and Analysis of Quantitative Traits. Sinauer, Sunderland, MA, USA.
  21. Mallinckrodt, C. H., B. L. Golden and R. M. Bourdon. 1995. The effect of selective reporting on estimates of weaning weight parameters in beef cattle. J. Anim. Sci. 73:1264-1270. https://doi.org/10.2527/1995.7351264x
  22. McCulloch, C. E. 1994. Maximum likelihood variance components estimation for binary data. J. Am. Stat. Assoc. 89:330-335. https://doi.org/10.2307/2291229
  23. Nelder, J. A. and R. W. M. Wedderburn. 1972. Generalized linear models. J. Roy. Stat. Soc. A. 135:370-384. https://doi.org/10.2307/2344614
  24. Patterson, H. D. and R. Thompson. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika 58:545-554. https://doi.org/10.1093/biomet/58.3.545
  25. Quaas, R. L. and E. J. Pollak. 1980. Mixed model methodology for farm and ranch beef cattle testing programs. J. Anim. Sci. 51:1277-1287. https://doi.org/10.2527/jas1981.5161277x
  26. San Cristobal, M., J. L. Foulley and E. Manfredi. 1993. Inference about multiplicative heteroskedastic components of variance in a mixed linear Gaussian model with an application to beef cattle breeding. Gene. Sel. Evol. 25:3-30. https://doi.org/10.1186/1297-9686-25-1-3
  27. Schenkel, F. S. and L. R. Schaeffer. 1998. Effects of non translation invariant selection on estimates of variance components. Proc. 6th World Cong. Genet. Appl. Livest. Prod., Armidale, 25:509-512.
  28. Searle, S. R., G. Casella and C. E. McCulloch. 1992. Variance Components. Wiley & Sons, New York.
  29. Smith, S. P. and H. -U. Graser. 1986. Estimating variance components in a class of mixed models by restricted maximum likelihood. J. Dairy Sci. 69:1156-1165. https://doi.org/10.3168/jds.S0022-0302(86)80516-1
  30. Sorenson, D. A., S. Anderson, D. Gianola and I. Korsgaard. 1995. Bayesian inference in threshold models using Gibbs sampling. Gene. Sel. Evol. 27:229-249. https://doi.org/10.1186/1297-9686-27-3-229
  31. Tempelman, R. J. and D. Gianola. 1993. Marginal maximum likelihood estimation of variance components in Poisson mixed models using Laplacian integration. Gene. Sel. Evol. 25:305-319. https://doi.org/10.1186/1297-9686-25-4-305
  32. Thaller, G. and I. Hoeschele. 1996. A Monte Carlo method for Bayesian analysis of linkage between single markers and quantitative trait loci. I. Methodology. Theor. Appl. Genet. 93:1161-1166. https://doi.org/10.1007/BF00230141
  33. Van Tassell, C. P., G. Casella and E. J. Pollak. 1995. Effects of selection on estimates of variance components using Gibbs sampling and restricted maximum likelihood. J. Dairy Sci. 78, 678-692. https://doi.org/10.3168/jds.S0022-0302(95)76680-2
  34. Van Tassell, C. P. and L. D. Van Vleck. 1996. Multiple-trait Gibbs sampler for animal models: flexible programs for Bayesian and likelihood-based (co)variance component inference. J. Anim. Sci. 74:2586-2597. https://doi.org/10.2527/1996.74112586x
  35. Walling, G. A., P. M. Visscher, L. Andersson, M. F. Rothschild, L. Wang, G. Moser, M. A. Groenen, J. P. Bidanel, S. Cepica, A. L. Archibald, H. Geldermann, D. J. de Koning, D. Milan and C. S. Haley. 2000. Combined analyses of data from quantitative trait loci mapping studies: Chromosome 4 effects on porcine growth and fatness. Genetics 155:1369-1378.
  36. Wang, C. S., J. J. Rutledge and D. Gianola. 1993. Marginal inferences about variance components in a mixed linear model using Gibbs sampling. Gene. Sel. Evol. 25:41-62. https://doi.org/10.1186/1297-9686-25-1-41
  37. Xu, S. and N. Yi. 2000. Mixed model analysis of quantitative trait loci. Proc. Natl. Acad. Sci. USA 97:14542-14547. https://doi.org/10.1073/pnas.250235197
  38. Zeng, Z. B. 1993. Theoretical basis of separation of multiple linked gene effects on mapping quantitative trait loci. Proc. Natl. Acad. Sci. USA 90:10972-10976. https://doi.org/10.1073/pnas.90.23.10972
  39. Zou, F, B. S. Yandell, and J. P. Fine. 2001. Statistical issues in the analysis of quantitative traits in combined crosses. Genetics 158:1339-1346.