Accuracy of genomewide selection for different traits with constant population size, heritability, and number of markers

Plant Genome

Volumn 6, Issue 1, 2013, Pages

  Combs, Emily ^a   Bernardo, Rex ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84884358531     PISSN: None     EISSN: 19403372     Source Type: Journal    
DOI: 10.3835/plantgenome2012.11.0030     Document Type: Article

References (37)

1. Albrecht, T., V. Wimmer, H. Auinger, M. Erbe, C. Knaak, M. Ouzunova, H. Simianer, and C. Schon. 2011. Genome-based prediction of testcross values in maize. Theor. Appl. Genet. 123:339-350.doi:10.1007/s00122-011-1587-7
2. Barrett, J.C., B. Fry, J. Maller, and M.J. Daly. 2005. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics 21:263-265.
3. Bernardo, R. 2010. Breeding for quantitative traits in plants. 2nd ed. Stemma Press, Woodbury, MN.
4. Bernardo, R., and J. Yu. 2007. Prospects for genomewide selection for quantitative traits in maize. Crop Sci. 47:1082-1090.doi:10.2135/ cropsci2006.11.0690
5. Daetwyler, H.D., R. Pong-Wong, B. Villanueva, and J.A. Woolliams. 2010. The impact of genetic architecture on genome-wide evaluation methods. Genetics 185:1021-1031.doi:10.1534/genetics.110.116855
6. Daetwyler, H.D., B. Villanueva, and J.A. Woolliams. 2008. Accuracy of predicting the genetic risk of disease using a genome-wide approach. PLoS ONE 3:e3395.doi:10.1371/journal.pone.0003395
7. Doerge, R., Z. Zeng, and B. Weir. 1994. Statistical issues in the search for genes aff ecting quantitative traits in populations. In: Statistical issues in the search for genes aff ecting quantitative traits in populations. Analysis of molecular marker data (supplement). Joint Plant Breed. Symp. Ser. Am. Soc. Hort. Sci., CSSA, Madison, WI. p. 15-26.
8. Endelman, J.B. 2011. Ridge regression and other kernels for genomic selection with R package rrBLUP. Plant Gen. 4:250-255.doi:10.3835/ plantgenome2011.08.0024
9. Goddard, M.E., and B.J. Hayes. 2007. Genomic selection. J. Anim. Breed. Genet. 124:323-330.doi:10.1111/j.1439-0388.2007.00702.x
10. Goddard, M.E., and B.J. Hayes. 2009. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nat. Rev. Genet. 10:381-391.doi:10.1038/nrg2575
11. Goddard, M., and B. Hayes. 2011. Using the genomic relationship matrix to predict the accuracy of genomic selection. J. Anim. Breed. Genet. 128:409-421.doi:10.1111/j.1439-0388.2011.00964.x
12. Grattapaglia, D., C. Plomion, M. Kirst, and R.R. Sederoff. 2009. Genomics of growth traits in forest trees. Curr. Opin. Plant Biol. 12:148-156.doi:10.1016/j.pbi.2008.12.008
13. Grattapaglia, D., and M.D.V. Resende. 2011. Genomic selection in forest tree breeding. Tree Genet. Genomes 7:241-255.doi:10.1007/s11295- 010-0328-4
14. Guo, Z., D.M. Tucker, J. Lu, V. Kishore, and G. Gay. 2012. Evaluation of genome-wide selection effi ciency in maize nested association mapping populations. Theor. Appl. Genet. 124:261-275.doi:10.1007/ s00122-011-1702-9
15. Hallauer, A.R., and J.B. Miranda Filho. 1981. Quantitative genetics in maize breeding. Iowa State Univ. Press, Ames, IA.
16. Hayes, B., and M. Goddard. 2010. Genome-wide association and genomic selection in animal breeding. Genome 53:876-883.doi:10.1139/G10-076
17. Hayes, P.M., B.H. Liu, S.J. Knapp, F. Chen, B. Jones, T. Blake, J. Franckowiak, D. Rasmusson, M. Sorrells, S.E. Ullrich, D. Wesenberg, and A. Kleinhofs. 1993. Quantitative trait locus eff ects and environmental interaction in a sample of North American barley germplasm. Theor. Appl. Genet. 87:392-401.doi:10.1007/BF01184929
18. Heff ner, E.L., J.L. Jannink, H. Iwata, E. Souza, and M.E. Sorrells. 2011. Genomic selection accuracy for grain quality traits in biparental wheat populations. Crop Sci. 51:2597-2606.doi:10.2135/ cropsci2011.05.0253
19. Heffner, E.L., J.L. Jannink, and M.E. Sorrells. 2011. Genomic selection accuracy using multifamily prediction models in a wheat breeding program. Plant Gen. 4:65-75.doi:10.3835/plantgenome.2010.12.0029
20. Holland, J.B. 2007. Genetic architecture of complex traits in plants. Curr. Opin. Plant Biol. 10:156-161.doi:10.1016/j.pbi.2007.01.003
21. Knapp, S., W. Stroup, and W. Ross. 1985. Exact confi dence intervals for heritability on a progeny mean basis. Crop Sci. 25:192-194.doi:10.2135/cropsci1985.0011183X002500010046x
22. Lande, R., and R. Th ompson. 1990. Effi ciency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743-756.
23. Lawrence, C.J., T.E. Seigfried, and V. Brendel. 2005. The maize genetics and genomics database. The community resource for access to diverse maize data. Plant Physiol. 138:55-58.doi:10.1104/pp.104.059196
24. Lee, M., N. Sharopova, W.D. Beavis, D. Grant, M. Katt, D. Blair, and A. Hallauer. 2002. Expanding the genetic map of maize with the intermated B73 × Mo17 (IBM) population. Plant Mol. Biol. 48:453-461.doi:10.1023/A:1014893521186
25. Lewis, M.F., R.E. Lorenzana, H.G. Jung, and R. Bernardo. 2010. Potential for simultaneous improvement of corn grain yield and stover quality for cellulosic ethanol. Crop Sci. 50:516-523.doi:10.2135/ cropsci2009.03.0148
26. Lorenz, A.J., S. Chao, F.G. Asoro, E.L. Heff ner, T. Hayashi, H. Iwata, K.P. Smith, M.E. Sorrells, and J. Jannink. 2011. Genomic selection in plant breeding: Knowledge and prospects. In: D.L. Sparks, editor, Advances in agronomy. Academic Press, Waltham, MA. p. 77-123.
27. Lorenzana, R., and R. Bernardo. 2009. Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theor. Appl. Genet. 120:151-161.doi:10.1007/s00122-009-1166-3
28. Meuwissen, T. 2012. The accuracy of genomic selection. 15theuropean Assoc. Plant Breed. Res. (EUCARPIA) Biometrics in Plant Breed. Section Mtg., Stuttgart, Germany. 5-7 Sept. 2012. University of Hohenheim, Stuttgart, Germany. https://www.uni-hohenheim.de/fi leadmin/einrichtungen/eucarpia-biometrics-2012/pdf-Dateien/Programmheft_Eucarpia_20.8.12.pdf (accessed 24 Aug. 2012). p. 26.
29. Meuwissen, T.H.E., B.J. Hayes, and M.E. Goddard. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819-1829.
30. Myles, S., J. Peiff er, P.J. Brown, E.S. Ersoz, Z. Zhang, D.E. Costich, and E.S. Buckler. 2009. Association mapping: Critical considerations shift from genotyping to experimental design. Plant Cell 21:2194-2202.doi:10.1105/tpc.109.068437
31. R Deve lopment Core Team. 2012. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/ (accessed 10 July 2012).
32. Resende, M., Jr., P. Muñoz, M.D.V. Resende, D.J. Garrick, R.L. Fernando, J.M. Davis, E.J. Jokela, T.A. Martin, G.F. Peter, and M. Kirst. 2012. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.). Genetics 190:1503-1510.doi:10.1534/ genetics.111.137026
33. SAS Institute. 2009. The SAS system for Windows. Release 9.2. SAS Inst., Cary, NC.
34. Senior, M., E. Chin, M. Lee, J. Smith, and C. Stuber. 1996. Simple sequence repeat markers developed from maize sequences found in the GENBANK database: Map construction. Crop Sci. 36:1676-1683.doi:10.2135/cropsci1996.0011183X003600060043x
35. Somers, D.J., P. Isaac, and K. Edwards. 2004. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor. Appl. Genet. 109:1105-1114.doi:10.1007/s00122-004-1740-7
36. USDA-ARS. 2008. GrainGenes: A database for Triticeae and Avena. USDA-ARS, Washington, DC. http://wheat.pw.usda.gov/GG2/index. shtml (accessed 4 Oct. 2008).
37. Zhong, S., J.C.M. Dekkers, R.L. Fernando, and J. Jannink. 2009. Factors aff ecting accuracy from genomic selection in populations derived from multiple inbred lines: A barley case study. Genetics 182:355-364.doi:10.1534/genetics.108.098277