JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Predicting the Accuracy of Breeding Values Using High Density Genome Scans
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Predicting the Accuracy of Breeding Values Using High Density Genome Scans
Lee, Deuk-Hwan; Vasco, Daniel A.;
  PDF(new window)
 Abstract
In this paper, simulation was used to determine accuracies of genomic breeding values for polygenic traits associated with many thousands of markers obtained from high density genome scans. The statistical approach was based upon stochastically simulating a pedigree with a specified base population and a specified set of population parameters including the effective and noneffective marker distances and generation time. For this population, marker and quantitative trait locus (QTL) genotypes were generated using either a single linkage group or multiple linkage group model. Single nucleotide polymorphism (SNP) was simulated for an entire bovine genome (except for the sex chromosome, n
 Keywords
Simulationbased Inference;Prediction Accuracy;Breeding Value;High Density Genome Scan;Single Nucleotide Polymorphism;
 Language
English
 Cited by
1.
Genomic selection using beef commercial carcass phenotypes, animal, 2014, 8, 03, 388  crossref(new windwow)
 References
1.
Aguitar, I. and I. Misztal. 2008. Technical note: Recursive algorithm for inbreeding coefficients assuming nonzero inbreeding of unknown parents. J. Dairy Sci. 91:1669-1672. crossref(new window)

2.
Bailey, N. T. J. 1961. Introduction to the Mathematical Theory of Genetic Linkage. Oxford Universisty press.

3.
Barendse, W., D. Vaiman, S. J. Kemp, Y. Sugimoto, S. M. Armitage, J. L. Williams, H. S. Sun, A. Eggen, M. Agaba, S. A. Aleyasin, M. Band, M. D. Bishop, J. Buitkamp, K. Byrne, F. Collins, L. Cooper, W. Coppettiers, B. Denys, R. D. Drinkwater, K. Easterday, C. Elduque, S. Ennis, G. Erhardt, L. Ferretti, N. Flavin, Q. Gao, M. Georges, R. Gurung, B. Harlizius, G. Hawkins, J. Hetzel, T. Hirano, D. Hulme, C. Jorgensen, M. Kessler, B. W. Kirkpatrick, B. Konfortov, S. Kostia, C. Kuhn, J. A. Lenstra, H. Leveziel, H. A. Lewin, B. Leyhe, L. Lil, I. Martin Burriel, McGraw, J. R. Miller, D. E. Moody, S. S. Moore, S. Nakane, I. J. Nijman, I. Olsaker, D. Pomp, A. Rando, M. Ron, A. Shalom, A. J. Teale, U. Thieven, B. G. D. Urquhart, D.-I. Vage, A. Van de Weghe, S. Varvio, R. Velmala, J. Vilkki, R. Weikard, C. Woodside, J. E. Womack, M. Zanotti and Zaragoza. 1997. A medium-density genetic linkage map of the bovine genome. Mamm. Genome 8:21-28. crossref(new window)

4.
Blouin, M. S. 2003. DNA-based methods for pedigree reconstruction and kinship analysis in natural populations, Trends Ecol. Evol. 18:503-511. crossref(new window)

5.
Calus, M. P. L., T. H. E. Meuwissen, A. P. W. de Roos and R. F. Veerkamp. 2008. Accuracy of genomic selection using different methods to define haplotypes. Genetics 178:553-561. crossref(new window)

6.
De Roos, A. P. W., B. J. Hayes, R. J. Spelman and M. E. Goddard. 2008. Linkage disequilibrium and persistence of phase in Holstein-Friesian, Jersey and Angus cattle. Genetics 179:1503-1512 crossref(new window)

7.
Falconer, D. S. and T. F. C. Mackay. 1996. Introduction to quantitative genetics. Longman Group, Essex, UK.

8.
Gasbarra, D., M. J. Sillanpaa and E. Arjas. 2005 Backward simulation of ancestors of sampled individuals. Theor. Popul. Biol. 67:75-83. crossref(new window)

9.
Guttorp, P. 1995. Stochastic modeling of scientific data. Chapman and Hall, CRC press.

10.
Hayes, B. J. and M. E. Goddard. 2001. The distribution of the effects of genes affecting quantitative traits in livestock. Genet. Sel. Evol. 33:209-229. crossref(new window)

11.
Hayes, B. J. and M. E. Goddard. 2008. Technical note: Prediction of breeding values using marker-derived relationship matrices. J. Anim. Sci. 86:2089-2092. crossref(new window)

12.
Hill, W. G. and B. S. Weir. 2007. Prediction of multi-locus inbreeding coeffcients and relation to linkage disequilibrium in random mating populations. Theor. Popul. Biol. 72:179-185. crossref(new window)

13.
Libiger, O. and N. J. Schork. 2007. A simulation-based analysis of chromosome segment sharing among a group of arbitrarily related individuals. Eur. J. Hum. Genet. 15:1260-1268. crossref(new window)

14.
Liu, B-H. 1998. Statisitical genomics. CRC press.

15.
Lynch, M. and B. Walch. 1998. Genetics and analysis of quantitative traits. Sinauer Associates Inc, Sunderland, MA.

16.
Macleod, I. M., B. J. Hayes and M. E. Goddard. 2006 Efficiency of dense bovine single-nucleotide polymorphisms to detect and position quantitative trait loci. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Brazil, August 13-18, 2006. CD-ROM communication no. 20-04.

17.
Matukumalli, L. K., C. T. Lawley, R. D. Schnabel, J. F. Taylor, M. F. Allan, M. P. Heaton, J. O'Connell, T. S. Sonstegard, T. P. L. Smith, S. S. Moore and C. P. Van Tassell. 2009. Development and characterization of a high density SNP genotyping assay for cattle. PLoS One. (submitted).

18.
Meuwissen, T. H. E., B. Hayes and M. E. Goddard. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819-1829.

19.
Peng, B., C. I. Amos and M. Kimmel. 2007. Forward-time simulations of human populations with complex diseases. PLoS Genetics 3:e47. crossref(new window)

20.
Peng, B. and M. Kimmel. 2005. SimuPOP: a forward-time population genetics simulation environment. Bioinformatics 21:3686-3687. crossref(new window)

21.
Quass, R. L. 1976. Computing the diagonal elements and inverse of a large numerator relationship matrix. Biometrics 32:949-953. crossref(new window)

22.
Schaeffer, L. R. 2006. Strategy for applying genome-wide selection in dairy cattle. J. Anim. Breed. Genet. 123:218-223. crossref(new window)

23.
Solberg, T. R., A. K. Sonesson, J. A. Woolliams and T. H. E. Meuwissen. 2008. Genomic selection using different marker types and densities. J. Anim. Sci. 86:2447-2454. crossref(new window)

24.
Strand, A. E. 2002. METASIM 1.0: an individual-based environment for simulating population genetics of complex population dynamics. Mol. Ecol. Notes 2:373-376. crossref(new window)

25.
Tenesa, A., P. Navarro, B. J. Hayes, D. L. Duffy, G. M. Clarke, M. E. Goddard and P. M. Visscher. 2007. Recent human effective population size estimated from linkage disequilibrium. Genome Res. 17:520-526. crossref(new window)

26.
TeMeerman, G. J. and M. A. Van der Meulen. 1997. Genomic sharing surrounding alleles identical by descent: effects of genetic drift and population growth. Genet. Epidemiol. 14:1125-1130. crossref(new window)

27.
VanRaden, P. M. 2007. Genomic measures of relationship and inbreeding. INTERBULL bulletin. 37: 33-36

28.
VanRaden, P. M. 2008. Efficient methods to compute genomic predictions. J. Dairy Sci. 91:4414-4423. crossref(new window)

29.
VanRaden, P. M., C. P. Van Tassell, G. R. Wiggans, T. S. Sonstegard, R. D. Schnabel, J. F. Taylor and F. S. Schenkel. 2009. Invited review: Reliability of genomic prediction for north american Holstein bulls. J. Dairy Sci. 92:16-24. crossref(new window)

30.
Van Tassell, C. P., T. P. L. Smith, L. K. Matukumallik, J. F. Taylor, R. D. Schnabel, C. T. Lawley, C. D. Haudenschild, S. S. Moore, W. C. Warren and T. S. Sonstegard. 2008. SNP discovery and allele frequency estimation by deep sequencing of reduced representation libraries. Nat. Methods 5:247-252. crossref(new window)

31.
Villanueva, B., R. Pong-Wong, J. Fernandez and M. A. Toro. 2005. Benefits from marker-assisted selection under an additive polygenic genetic model. J. Anim. Sci. 83:1747-1752.

32.
Visscher, P. M., S. E. Medland, M. A. Ferreira, K. I. Morley, G. Zhu, B. K. Cornes, G. W. Montgomery and N. G. Martin. 2006. Assumption-free estimation of heritability from genome-wide identity-by-descent sharing between full siblings. PLoS Genet. 2:e4. crossref(new window)

33.
Wu, R., C-X Ma and G. Casella. 2007. Statistical genetics of quantitative traits. Springer.