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BioMed Research International
Volume 2016 (2016), Article ID 5761983, 13 pages
http://dx.doi.org/10.1155/2016/5761983
Research Article

-Index for Differentiating Complex Dynamic Traits

1School of Information, Beijing Forestry University, Beijing 100083, China
2Center for Computational Biology, Beijing Forestry University, Beijing 100083, China

Received 3 July 2015; Revised 28 October 2015; Accepted 11 February 2016

Academic Editor: Sílvia A. Sousa

Copyright © 2016 Jiandong Qi 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. T. F. C. MacKay, E. A. Stone, and J. F. Ayroles, “The genetics of quantitative traits: challenges and prospects,” Nature Reviews Genetics, vol. 10, no. 8, pp. 565–577, 2009. View at Publisher · View at Google Scholar · View at Scopus
  2. E. S. Lander and S. Botstein, “Mapping mendelian factors underlying quantitative traits using RFLP linkage maps,” Genetics, vol. 121, no. 1, pp. 185–199, 1989. View at Google Scholar · View at Scopus
  3. C. Neuschl, G. A. Brockmann, and S. A. Knott, “Multiple-trait QTL mapping for body and organ weights in a cross between NMRI8 and DBA/2 mice,” Genetical Research, vol. 89, no. 1, pp. 47–59, 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. L. J. Leamy, D. Pomp, E. J. Eisen, and J. M. Cheverud, “Pleiotropy of quantitative trait loci for organ weights and limb bone lengths in mice,” Physiological Genomics, vol. 2002, no. 10, pp. 21–29, 2002. View at Google Scholar · View at Scopus
  5. C. Fan, Y. Xing, H. Mao et al., “GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein,” Theoretical and Applied Genetics, vol. 112, no. 6, pp. 1164–1171, 2006. View at Publisher · View at Google Scholar · View at Scopus
  6. G. Shao, S. Tang, J. Luo et al., “Mapping of qGL7-2, a grain length QTL on chromosome 7 of rice,” Journal of Genetics and Genomics, vol. 37, no. 8, pp. 523–531, 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. P. Ramya, A. Chaubal, K. Kulkarni et al., “QTL mapping of 1000-kernel weight, kernel length, and kernel width in bread wheat (Triticum aestivum L.),” Journal of Applied Genetics, vol. 51, no. 4, pp. 421–429, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. X. Y. Wan, J. M. Wan, L. Jiang et al., “QTL analysis for rice grain length and fine mapping of an identified QTL with stable and major effects,” Theoretical and Applied Genetics, vol. 112, no. 7, pp. 1258–1270, 2006. View at Publisher · View at Google Scholar · View at Scopus
  9. R. L. Wu and M. Lin, “Opinion: Functional mapping—how to map and study the genetic architecture of dynamic complex traits,” Nature Reviews Genetics, vol. 7, no. 3, pp. 229–237, 2006. View at Publisher · View at Google Scholar · View at Scopus
  10. M. Kirkpatrick and N. Heckman, “A quantitative genetic model for growth, shape, reaction norms, and other infinite-dimensional characters,” Journal of Mathematical Biology, vol. 27, no. 4, pp. 429–450, 1989. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  11. S. D. Pletcher and C. J. Geyer, “The genetic analysis of age-dependent traits: modeling the character process,” Genetics, vol. 153, no. 2, pp. 825–835, 1999. View at Google Scholar · View at Scopus
  12. R.-L. Wu, M.-X. Wang, and M.-R. Huang, “Quantitative genetics of yield breeding for Populus short rotation culture. I. Dynamics of genetic control and selection model of yield traits,” Canadian Journal of Forest Research, vol. 22, no. 2, pp. 175–182, 1992. View at Publisher · View at Google Scholar
  13. W. R. Atchley and J. Zhu, “Developmental quantitative genetics, conditional epigenetic variability and growth in mice,” Genetics, vol. 147, no. 2, pp. 765–776, 1997. View at Google Scholar · View at Scopus
  14. J. M. Cheverud, J. J. Rutledge, and W. R. Atchley, “Quantitative genetics of development: genetic correlations among age-specific trait values and the evolution of ontogeny,” Evolution, vol. 37, no. 5, pp. 895–905, 1983. View at Publisher · View at Google Scholar
  15. W. R. Atchley, “Ontogeny, timing of development, and genetic variance-covariances structure,” The American Naturalist, vol. 123, no. 4, pp. 519–540, 1984. View at Publisher · View at Google Scholar · View at Scopus
  16. W.-R. Wu, W.-M. Li, D.-Z. Tang, H.-R. Lu, and A. J. Worland, “Time-related mapping of quantitative trait loci underlying tiller number in rice,” Genetics, vol. 151, no. 1, pp. 297–303, 1999. View at Google Scholar · View at Scopus
  17. J. M. Cheverud, E. J. Routman, F. A. M. Duarte, B. Van Swinderen, K. Cothran, and C. Perel, “Quantitative trait loci for murine growth,” Genetics, vol. 142, no. 4, pp. 1305–1319, 1996. View at Google Scholar · View at Scopus
  18. D. Verhaegen, C. Plomion, J.-M. Gion, M. Poitel, P. Costa, and A. Kremer, “Quantitative trait dissection analysis in Eucalyptus using RAPD markers. 1. Detection of QTL in interspecific hybrid progeny, stability of QTL expression across different ages,” Theoretical and Applied Genetics, vol. 95, no. 4, pp. 597–608, 1997. View at Publisher · View at Google Scholar · View at Scopus
  19. L. C. Emebiri, M. E. Devey, A. C. Matheson, and M. U. Slee, “Age-related changes in the expression of QTLs for growth in radiata pine seedlings,” Theoretical and Applied Genetics, vol. 97, no. 7, pp. 1053–1061, 1998. View at Publisher · View at Google Scholar · View at Scopus
  20. B. Mangin, P. Thoquet, and N. Grimsley, “Pleiotropic QTL analysis,” Biometrics, vol. 54, no. 1, pp. 88–99, 1998. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  21. A. B. Korol, Y. I. Ronin, A. M. Itskovich, J. Peng, and E. Nevo, “Enhanced efficiency of quantitative trait loci mapping analysis based on multivariate complexes of quantitative traits,” Genetics, vol. 157, no. 4, pp. 1789–1803, 2001. View at Google Scholar · View at Scopus
  22. C. X. Ma, G. Casella, and R. L. Wu, “Functional mapping of quantitative trait loci underlying the character process: a theoretical framework,” Theoretical and Applied Genetics, vol. 97, no. 7, pp. 1053–1061, 1998. View at Google Scholar
  23. G. B. West, J. H. Brown, and B. J. Enquist, “A general model for ontogenetic growth,” Nature, vol. 413, no. 6856, pp. 628–631, 2001. View at Publisher · View at Google Scholar · View at Scopus
  24. R. L. Wu, C.-X. Ma, X.-Y. Lou, and G. Casella, “Molecular dissection of allometry, ontogeny, and plasticity: a genomic view of developmental biology,” BioScience, vol. 53, no. 11, pp. 1041–1047, 2003. View at Publisher · View at Google Scholar · View at Scopus
  25. R. L. Wu, C.-X. Ma, M. Lin, and G. Casella, “A general framework for analyzing the genetic architecture of developmental characteristics,” Genetics, vol. 166, no. 3, pp. 1541–1551, 2004. View at Publisher · View at Google Scholar · View at Scopus
  26. R. Wu, C.-X. Ma, R. C. Littell, and G. Casella, “A statistical model for the genetic origin of allometric scaling laws in biology,” Journal of Theoretical Biology, vol. 219, no. 1, pp. 121–135, 2002. View at Publisher · View at Google Scholar · View at Scopus
  27. R. L. Wu, C.-X. Ma, M. Lin, Z. Wang, and G. Casella, “Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model,” Biometrics, vol. 60, no. 3, pp. 729–738, 2004. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  28. R. L. Wu, Z. H. Wang, W. Zhao, and J. M. Cheverud, “A mechanistic model for genetic machinery of ontogenetic growth,” Genetics, vol. 168, no. 4, pp. 2383–2394, 2004. View at Publisher · View at Google Scholar · View at Scopus
  29. X. Zhao, C. Tong, X. Pang et al., “Functional mapping of ontogeny in flowering plants,” Briefings in Bioinformatics, vol. 13, no. 3, pp. 317–328, 2012. View at Publisher · View at Google Scholar · View at Scopus
  30. L. Jiang, J. Liu, X. Zhu et al., “2HiGWAS: a unifying high-dimensional platform to infer the global genetic architecture of trait development,” Briefings in Bioinformatics, vol. 16, no. 6, pp. 905–911, 2015. View at Publisher · View at Google Scholar
  31. L. Bogin, Patterns of Human Growth, Cambridge University Press, 2nd edition, 1999.
  32. M. Liu, X. Li, R. Fan, X. Liu, and J. Wang, “A systematic analysis of candidate genes associated with nicotine addiction,” BioMed Research International, vol. 2015, Article ID 313709, 9 pages, 2015. View at Publisher · View at Google Scholar