Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: A simulation experiment

G3: Genes, Genomes, Genetics

Volumn 3, Issue 3, 2013, Pages 481-491

  Lorenz, Aaron J ^a  

^a UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Genomic; Genpred; Plant breeding; Resources; Selection; Shared data

Indexed keywords

MARKER;

ACCURACY; ALLELE; ARTICLE; BREEDING; COMPUTER SIMULATION; DOUBLED HAPLOID LINE; GENE LINKAGE DISEQUILIBRIUM; GENE MAPPING; GENETIC DISTANCE; GENETIC GAIN; GENETIC SELECTION; GENETIC VARIABILITY; GENETICS; GENOMIC SELECTION; GENOTYPE; GENPRED; HAPLOIDY; HERITABILITY; INHERITANCE; MAIZE; METHODOLOGY; NONHUMAN; PHENOTYPE; PHYSIOLOGY; PLANT BREEDING; PLANT CHROMOSOME; PLANT GENOME; POPULATION SIZE; PREDICTION; QUANTITATIVE GENETICS; QUANTITATIVE TRAIT LOCUS; REGRESSION ANALYSIS; REPRODUCIBILITY; RESOURCE ALLOCATION; SENSITIVITY AND SPECIFICITY; SHARED DATA RESOURCES; SINGLE NUCLEOTIDE POLYMORPHISM;

EID: 84883222798     PISSN: None     EISSN: 21601836     Source Type: Journal    
DOI: 10.1534/g3.112.004911     Document Type: Article

References (30)

1. Albrecht, T.,V. Wimmer, H. Auinger, M. Erbe, C. Knaak et al., 2011 Genomebased prediction of testcross values in maize. Theor. Appl. Genet. 123: 339-350.
2. Beavis, W. D., 1994 The power and deceit of QTL experiments: lessons from comparative QTL studies, pp. 250-265 in Proceedings of the 49th Annual Corn and Sorghum Research Conference, edited by D. B. Wilkinson. American Seed Trade Association, Washington, DC.
3. Bernardo, R., 2008 Molecular markers and selection for complex traits in plants: learning from the last 20 years. Crop Sci. 48: 1649-1664.
4. Bernardo, R., 2010 Breeding for Quantitative Traits in Plants. Stemma Press, Woodbury, MN.
5. Bernardo, R., and J. Yu, 2007 Prospects for genome-wide selection for quantitative traits in maize. Crop Sci. 47: 1090.
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: 10.
7. Endelman, J. B., 2011 Ridge regression and other kernels for genomic selection with R package rrBLUP. The Plant Genome 4: 250-255.
8. Gimelfarb, A., and R. Lande, 1994 Simulation of marker assisted selection in hybrid populations. Genet. Res. 63: 39-47.
9. Goddard, M., 2009 Genomic selection: prediction of accuracy and maximisation of long term response. Genetica 136: 245-257.
10. Goddard, M. E., B. J. Hayes, and T. H. E. Meuwissen, 2011 Using the genomic relationship matrix to predict the accuracy of genomic selection. J. Anim. Breed. Genet. 128: 409-421.
11. Habier, D., R. L. Fernando, and J. C. M. Dekkers, 2007 The impact of genetic relationship information on genome-assisted breeding values. Genetics 177: 2389-2397.
12. Habier, D., R. L. Fernando, K. Kizilkaya, and D. J. Garrick, 2011 Extension of the Bayesian alphabet for genomic selection. BMC Bioinformatics 12: 186.
13. Hayes, B. J., P. M. Visscher, and M. E. Goddard, 2009 Increased accuracy of artificial selection by using the realized relationship matrix. Genet. Res. 91: 47-60.
14. Heffner, E. L., A. J. Lorenz, J. Jannink, and M. E. Sorrells, 2010 Plant breeding with genomic selection: gain per unit time and cost. Crop Sci. 50: 1681-1690.
15. Heffner, E. L., J. 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.
16. Jannink, J., 2010 Dynamics of long-term genomic selection. Genet. Sel. Evol. 42: 35.
17. Kang, H. M., N. A. Zaitlen, C. M. Wade, A. Kirby, D. Heckerman et al., 2008 Efficient control of population structure in model organism association mapping. Genetics 178: 1709-1723.
18. Kizilkaya, K., R. L. Fernando, and D. J. Garrick, 2010 Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes. J. Anim. Sci. 88: 544-551.
19. Knapp, S. J., and W. C. Bridges, 1990 Using molecular markers to estimate quantitative trait locus parameters: Power and genetic variances for unreplicated and replicated progeny. Genetics 126: 769-777.
20. Lorenz, A. J., K. P. Smith, and J.-L. Jannink, 2012 Potential and optimization of genomic selection for Fusarium head blight resistance in six-row barley. Crop Sci. 52: 1609-1621.
21. Lorenzana, R. E., and R. Bernardo, 2009 Accuracy of genotypic value predictions for marker-based selection in biparental plant populations. Theor. Appl. Genet. 120: 151-161.
22. Lynch, M., and B. Walsh, 1998 Genetics and Analysis of Quantitative Traits. Sinauer Associates, Sunderland, MA.
23. Melchinger, A. E., H. F. Utz, and C. C. Schon, 1998 Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics 149: 383-403.
24. Moreau, L., S. Lemarie, A. Charcosset, and A. Gallais, 2000 Economic efficiency of one cycle of marker-assisted selection. Crop Sci. 40: 329-337.
25. Riedelsheimer, C., A. Czedik-Eysenberg, C. Grieder, J. Lisec, F. Technow et al., 2012 Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat. Genet. 44: 217-220.
26. Schon, C. C., H. F. Utz, S. Groh, B. Truberg, S. Openshaw et al., 2004 Quantitative trait locus mapping based on resampling in a vast maize testcross experiment and its relevance to quantitative genetics for complex traits. Genetics 167: 485-498.
27. Utz, H., A. Melchinger, and C. Schon, 2000 Bias and sampling error of the estimated proportion of genotypic variance explained by quantitative trait loci determined from experimental data in maize using cross validation and validation with independent samples. Genetics 154: 1839-1849.
28. Wricke, G., and W. E. Weber, 1986 Quantitative Genetics and Selection in Plant Breeding. Walter de Gruyter & Co., Berlin.
29. Yu, J., J. B. Holland, M. D. McMullen, and E. S. Buckler, 2008 Genetic design and statistical power of nested association mapping in maize. Genetics 178: 539-551.
30. Zhong, S., J. C. M. Dekkers, R. L. Fernando, and J. L. Jannink, 2009 Factors affecting accuracy from genomic selection in populations derived from multiple inbred lines: a barley case study. Genetics 182: 355-364.