Genomic selection allowing for marker-by-environment interaction

Plant Breeding

Volumn 132, Issue 6, 2013, Pages 532-538

  Schulz Streeck, Torben ^a,b   Ogutu, Joseph O ^a   Gordillo, Andrés ^c,d   Karaman, Zivan ^e   Knaak, Carsten ^b   Piepho, Hans Peter ^a  

^a UNIVERSITY OF HOHENHEIM   (Germany)

^b KWS SAAT AG ^*  (Germany)

^c AgReliant Genetics LLC   (United States)

^d KWS LOCHOW GMBH ^*  (Germany)

^e Zone Indust de la Métairie   (France)

Author keywords

Genomic selection; Genotype by environment interaction; Marker by environment interaction; Ridge regression BLUP

Indexed keywords

EID: 84901270045     PISSN: 01799541     EISSN: 14390523     Source Type: Journal    
DOI: 10.1111/pbr.12105     Document Type: Article

References (27)

1. Albrecht, T., V. Wimmer, H. J. Auinger, M. Erbe, C. Knaak, M. Ouzunova, H. Simianer, and C. C. Schön, 2011: Genome-based prediction of testcross values in maize. Theor. Appl. Genet. 123, 339-350.
2. Atlin, G. N., R. J. Baker, K. B. McRae, and X. Lu, 2000: Selection response in subdivided target regions. Crop Sci. 40, 7-13.
3. Bernardo, R., and J. Yu, 2007: Prospects for genomewide selection for quantitative traits in maize. Crop Sci. 47, 1082-1090.
4. Burgueño, J., J. Crossa, J. M. Cotes, F. San Vicente, and B. Das, 2011: Prediction assessment of linear mixed models for multienvironment trials. Crop Sci. 51, 944-954.
5. Burgueño, J., G. de los Campos, K. Weigel, and J. Crossa, 2012: Genomic prediction of breeding values when modeling genotype × environment interaction using pedigree and dense molecular markers. Crop Sci. 52, 707-719.
6. Crossa, J., G. de los Campos, P. Pérez, D. Gianola, G. Atlin, J. Burgueño, J. L. Araus, D. Makumbi, J. Yan, V. Arief, M. Banziger, and H. J. Braun, 2010: Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers. Genetics 186, 713-724.
7. Denis, J. B., H. P. Piepho, and F. A. van Eeuwijk, 1997: Modelling expectation and variance for genotype by environment data. Heredity 79, 162-171.
8. Hayes, B. J., P. J. Bowman, A. J. Chamberlain, and M. E. Goddard, 2009: Genomic selection in dairy cattle: progress and challenges. J. Dairy Sci. 92, 433-443.
9. Jannink, J. L., 2010: Dynamics of long-term genomic selection. Genet. Sel. Evol. 42, 35.
10. 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.
11. 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.
12. Piepho, H. P., 1998: Empirical best linear unbiased prediction in cultivar trials using factor analytic variance-covariance structures. Theor. Appl. Genet. 97, 195-201.
13. Piepho, H. P., 2005: Statistical tests for QTL and QTL-by-environment effects in segregating populations derived from line crosses. Theor. Appl. Genet. 110, 561-566.
14. Piepho, H. P., 2009: Ridge regression and extensions for genome-wide selection in maize. Crop Sci. 49, 1165-1176.
15. Piepho, H. P., and J. Möhring, 2005: Best linear unbiased prediction for subdivided target regions. Crop Sci. 45, 1151-1159.
16. Piepho, H. P., and J. Möhring, 2007: Computing heritability and selection response from unbalanced plant breeding trials. Genetics 177, 1881-1888.
17. Piepho, H. P., and J.O. Ogutu, 2002: A simple mixed model for trend analysis in wildlife populations. J. Agric. Biol. Environ. Stat. 7, 350-360.
18. Piepho, H. P., E. R. Williams, and M. Fleck, 2006: A note on the analysis of designed experiments with complex treatment structure. HortScience 41, 446-452.
19. Piepho, H.P., J. Möhring, T. Schulz-Streeck, and J.O. Ogutu, 2012: A stage-wise approach for analysis of multi-environment trials. Biom. J. 54, 846-860.
20. Riedelsheimer, C., A. Czedik-Eysenberg, C. Grieder, J. Lisec, F. Technow, R. Sulpice, T. Altmann, M. Stitt, L. Willmitzer, and M. E. Melchinger, 2012: Genomic and metabolic prediction of complex heterotic traits in hybrid maize. Nat. Genet. 44, 217-220.
21. Schulz-Streeck, T., J. O. Ogutu, and H. P. Piepho, 2011: Pre-selection of markers for genomic selection. BMC Proc. 5(Suppl. 3), S12.
22. Schulz-Streeck, T., J. O. Ogutu, and H. P. Piepho, 2012: Comparisons of single-stage and two-stage approaches to genomic selection. Theor. Appl. Genet. 126, 69-82.
23. Szymczak, S., B. W. Igl, and A. Ziegler, 2009: Detecting SNP-expression associations: a comparison of mutual information and median test with standard statistical approaches. Stat. Med. 28, 3581-35962.
24. Utz, H. F., A. E. Melchinger, and C. C. Schön, 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.
25. Van Eeuwijk, F. A., J. Crossa, M. Vargas, and J. M. Ribaut, 2002: Analysing QTL-environment interaction by factorial regression, with an application to the CIMMYT drought and low-nitrogen stress programme in maize. In: M. S. Kang (ed.), Quantitative Genetics, Genomics and Plant Breeding, 245-256. CABI, Wallingford.
26. Weigel, K. A., G. de los Campos, O. González-Recio, H. Naya, X. L. Wu, N. Long, G. J. Rosa, and D. Gianola, 2009: Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers. J. Dairy Sci. 92, 5248-5257.
27. Zhao, Y., M. Gowda, W. Liu, T. Würschum, H. P. Maurer, F. H. Longin, N. Ranc, and J. C. Reif, 2011: Accuracy of genomic selection in European maize elite breeding Populations. Theor. Appl. Genet. 124, 769-776.