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The Scientific World Journal
Volume 2014 (2014), Article ID 924348, 9 pages
http://dx.doi.org/10.1155/2014/924348
Research Article

Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials

1Department of Agriculture, Federal University of Lavras, 3037 Lavras, MG, Brazil
2Department of Exact Sciences, Federal University of Lavras, 3037 Lavras, MG, Brazil

Received 6 March 2014; Revised 23 May 2014; Accepted 4 June 2014; Published 3 July 2014

Academic Editor: Yuehua Cui

Copyright © 2014 Wagner Mateus Costa Melo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. R. Hallauer, M. J. Carena, and J. B. Miranda-Filho, Quantitative Genetics in Maize Breeding, Springer, New York, NY, USA, 2010.
  2. J. S. de S. Bueno Filho and S. G. Gilmour, “Planning incomplete block experiments when treatments are genetically related,” Biometrics, vol. 59, no. 2, pp. 375–381, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. R. Bernardo, “Prediction of maize single-cross performance using RFLPs and information from related hybrids,” Crop Science, vol. 34, no. 1, pp. 20–25, 1994. View at Publisher · View at Google Scholar · View at Scopus
  4. A. E. Melchinger, “Genetic diversity and heterosis,” in The Genetics and Exploitation of Heterosis in Crops, J. G. Coors and S. Pandey, Eds., ASA, Madison, Wis, USA, 1999. View at Google Scholar
  5. S. Smith, S. Luk, B. Sobral, S. Muhawish, J. Peleman, and M. Zabeau, “Association among inbred lines of maize using RFLP and amplification technologies (AFLP and AP-PCR) and correlations with pedigree, F1yield, and heterosis,” Maize Genetics Newsletter, vol. 68, pp. 1–45, 1994. View at Google Scholar
  6. L. L. B. Lanza, C. L. de Souza Jr., L. M. M. Ottoboni, M. L. C. Vieira, and A. P. de Souza, “Genetic distance of inbred lines and prediction of maize single-cross performance using RAPD markers,” Theoretical and Applied Genetics, vol. 94, no. 8, pp. 1023–1030, 1997. View at Publisher · View at Google Scholar · View at Scopus
  7. A. M. M. Barbosa, I. O. Geraldi, L. L. Benchimol, A. A. F. Garcia, C. L. Souza Jr., and A. P. Souza, “Relationship of intra- and interpopulation tropical maize single cross hybrid performance and genetic distances computed from AFLP and SSR markers,” Euphytica, vol. 130, no. 1, pp. 87–99, 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. M. Balestre, J. C. Machado, J. L. Lima, J. C. Souza, and L. Nóbrega Filho, “Genetic distance estimates among single cross hybrids and correlation with specific combining ability and yield in corn double cross hybrids,” Genetics and Molecular Research, vol. 7, no. 1, pp. 65–73, 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. P. Devi and N. K. Singh, “Heterosis, molecular diversity, combining ability and their interrelationships in short duration maize (Zea mays L.) across the environments,” Euphytica, vol. 178, no. 1, pp. 71–81, 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. R. Di, M. X. Chu, Y. L. Li et al., “Predictive potential of microsatellite markers on heterosis of fecundity in crossbred sheep,” Molecular Biology Reports, vol. 39, no. 3, pp. 2761–2766, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. C. R. Henderson, “Specific and general combining ability,” in Heterosis, J. W. Gowen, Ed., Iowa State College Press, Ames, IA, USA, 1952. View at Google Scholar
  12. A. Charcosset, B. Bonnisseau, O. Touchebeuf et al., “Prediction of maize hybrid silage performance using marker data: comparison of several models for specific combining ability,” Crop Science, vol. 38, no. 1, pp. 38–44, 1998. View at Publisher · View at Google Scholar · View at Scopus
  13. T. A. Schrag, H. P. Maurer, A. E. Melchinger, H. Piepho, J. Peleman, and M. Frisch, “Prediction of single-cross hybrid performance in maize using haplotype blocks associated with QTL for grain yield,” Theoretical and Applied Genetics, vol. 114, no. 8, pp. 1345–1355, 2007. View at Publisher · View at Google Scholar · View at Scopus
  14. D. V. Ferreira, R. G. von Pinho, M. Balestre, and R. L. Oliveira, “Prediction of maize hybrid performance using similarity in state and similarity by descent information,” Genetics and Molecular Research, vol. 9, no. 4, pp. 2381–2394, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Gowda, Y. Zhao, H. P. Maurer, E. A. Weissmann, T. Würschum, and J. C. Reif, “Best linear unbiased prediction of triticale hybrid performance,” Euphytica, vol. 191, no. 2, pp. 223–230, 2013. View at Publisher · View at Google Scholar
  16. T. A. Schrag, J. Möhring, H. P. Maurer et al., “Molecular marker-based prediction of hybrid performance in maize using unbalanced data from multiple experiments with factorial crosses,” Theoretical and Applied Genetics, vol. 118, no. 4, pp. 741–751, 2009. View at Publisher · View at Google Scholar · View at Scopus
  17. T. A. Schrag, J. Möhring, A. E. Melchinger et al., “Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds,” Theoretical and Applied Genetics, vol. 120, no. 2, pp. 451–461, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. R. L. Fernando and D. Garrick, “Bayesian methods applied to GWAS,” Methods in Molecular Biology, vol. 1017, pp. 237–274, 2013. View at Publisher · View at Google Scholar · View at Scopus
  19. J. M. Massman, A. Gordillo, R. E. Lorenzana, and R. Bernardo, “Genomewide predictions from maize single-cross data,” Theoretical and Applied Genetics, vol. 126, no. 1, pp. 13–22, 2013. View at Publisher · View at Google Scholar · View at Scopus
  20. W. M. C. Melo, M. Balestre, R. G. Von Pinho, and J. S. S. Bueno-Filho, “Genetic control of the performance of maize hybrids using complex pedigrees and microsatellite markers,” Euphytica, vol. 195, no. 3, pp. 331–344, 2014. View at Google Scholar
  21. C. C. Cockerham, “Random and fixed effects in plant genetics,” Theoretical and Applied Genetics, vol. 56, no. 3, pp. 119–131, 1980. View at Publisher · View at Google Scholar · View at Scopus
  22. A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the EM algorithm,” Journal of the Royal Statistical Society, vol. 39, no. 1, pp. 1–38, 1977. View at Google Scholar · View at MathSciNet
  23. T. Sharot, “The generalized jackknife: finite samples and subsample sizes,” Journal of the American Statistical Association, vol. 71, no. 354, pp. 451–454, 1976. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  24. B. W. Legesse, A. A. Myburg, K. V. Pixley, S. Twumasi-Afriyie, and A. M. Botha, “Relationship between hybrid performance and AFLP based genetic distance in highland maize inbred lines,” Euphytica, vol. 162, no. 3, pp. 313–323, 2008. View at Publisher · View at Google Scholar · View at Scopus