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What Holds the Future of Quantitative Genetics? - A Review
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 Title & Authors
What Holds the Future of Quantitative Genetics? - A Review
Lee, Chaeyoung;
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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.
Complexities;Environmental Factors;Genetic Variances;Genome Projects;Quantitative Traits;
 Cited by
Quantitative Trait Loci Mapping for Fatty Acid Contents in the Backfat on Porcine Chromosomes 1, 13, and 18,이채영;정연승;김재홍;

Molecules and Cells, 2003. vol.15. 1, pp.62-62
Breslow, N. E. and D. G. Clayton. 1993. Approximate inference in generalized linear mixed models. J. Am. Stat. Assoc. 88:9-25. crossref(new window)

Casella, G. and R. L. Berger. 1990. Statistical Inference. Wadsworth and Brooks/Cole, Pacific Grove, CA.

Crow, J. F. and M. Kimura. 1970. An Introduction to Population Genetics Theory. Harper & Row, New York, NY, USA.

Fisher, R. A. 1925. Statistical methods for research workers. Oliver and Boyd, Edinburgh, England.

Fisher, R. A. 1930. The genetic thoery of natural selection. Dover, New York, NY, USA.

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.

Gianola, D. and R. L. Fernando. 1986. Bayesian methods in animal breeding theory. J. Anim. Sci. 63:217-244.

Hartley, H. O. and J. N. K. Rao. 1967. Maximum-likelihood estimation for the mixed analysis of variance model. Biomtrika 54:93-108.

Henderson, C. R. 1953. Estimation of variance and covariance components. Biometrics 9:226-252. crossref(new window)

Jensen, J. and I. L. Mao. 1991. Estimation of genetic parameters using sampled data from population undergoing selection. J. Dairy Sci. 74:3544-3551.

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.

Kao, C. H., Z. B. Zeng and R. D. Teasdale. 1999. Multiple interval mapping for quantitative trait loci. 152:1203-1216.

Lander, E. S. and D. Botstein. 1989. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185-199.

Lee, C. 2000a. Methods and techniques for variance component estimation in animal breeding. Asian-Aus. J. Anim. Sci. 13:413-422.

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.

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.

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.

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.

Lee, C. and E. J. Pollak. 2001. Genetic antagonism between body weight and milk production in beef cattle. J. Anim. Sci. (In press)

Lynch, M. and B. Walsh. 1998. Genetics and Analysis of Quantitative Traits. Sinauer, Sunderland, MA, USA.

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.

McCulloch, C. E. 1994. Maximum likelihood variance components estimation for binary data. J. Am. Stat. Assoc. 89:330-335. crossref(new window)

Nelder, J. A. and R. W. M. Wedderburn. 1972. Generalized linear models. J. Roy. Stat. Soc. A. 135:370-384. crossref(new window)

Patterson, H. D. and R. Thompson. 1971. Recovery of inter-block information when block sizes are unequal. Biometrika 58:545-554. crossref(new window)

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.

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. crossref(new window)

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.

Searle, S. R., G. Casella and C. E. McCulloch. 1992. Variance Components. Wiley & Sons, New York.

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.

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. crossref(new window)

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. crossref(new window)

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. crossref(new window)

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.

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.

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.

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. crossref(new window)

Xu, S. and N. Yi. 2000. Mixed model analysis of quantitative trait loci. Proc. Natl. Acad. Sci. USA 97:14542-14547. crossref(new window)

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. crossref(new window)

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.