Submit Manuscript

Journal of Biological Sciences

Year: 2001 | Volume: 1 | Issue: 8 | Page No.: 704-707
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail
Research Article

Diallel Analysis for Inbred Lines Involving Genotype × Environment Interaction Effects on Additive-Dominance Genetic Model

Abderrahmane Achouch and Zhu Jun

ABSTRACT

Additive-dominance genetic model was employed for eight inbred lines by mating design of modified diallel crosses with F1`s and reciprocal F1`s, F2`s and reciprocal F2`s. Monte Carlo simulations were conducted to compare specific effects and their interactions in single environment and in multiple environments when GE exits, when Genotype Environment (GE) is ignored and when it is null. Estimation of variance components and genetic prediction were computed by using respectively minimum norm quadratic unbiased estimation (MINQUE (1) and adjusted unbiased estimation (AUP). The genetic models in single and multiple environments were robust and gave unbiased estimates with high efficiencies. The variance residual s2Pwas significantly smaller and more efficient when GE interaction effects were considered in the full model. Whereas s2A, s2D and s2E were overestimated when s2AE and s2DE were ignored in the full model. If there are no genotype by environment interaction (GE) effects (s2AE =s2DE= 0), s2A and were estimated with similar bias, MSE and power value as when GE interaction effects are present. AUP method gave extremely low biases for mean of predicted genetic effects with absolute value between 8.10-5~12.10-4. When GE is not ignored, variance of prediction is significantly similar to the true value.
PDF References Citation

Search

REFERENCES

  1. Falconer, D.S. and T.F.C. Mackay, 1996. Introduction to Quantitative Genetics. 4th Edn., Prentice Hall, Harlow, England, ISBN-13: 9780582243026, Pages: 464.
    Direct Link
  2. Gardner, C.O. and S.A. Eberhart, 1966. Analysis and interpretation of the variety cross diallel and related populations. Biometrics, 22: 439-452.
    PubMedDirect Link
  3. Griffing, B., 1956. Concept of general and specific combining ability in relation to diallel crossing systems. Aust. J. Biol. Sci., 9: 463-493.
    Direct Link
  4. Weir, B.S., 1996. Genetic Data Analysis II. Sinauer Associates Inc., Sunderland, Massachusetts, pp: 445.
  5. Cockerham, C.C., 1980. Random and fixed effects in plant genetics. Theor. Applied Genet., 56: 119-131.
  6. Cockerham, C.C. and B.S. Weir, 1977. Quadratic analysis of reciprocal crosses. Biometrics, 33: 187-203.
  7. Hartley, H.D. and J.N.K. Rao, 1967. Maximum likelihood estimation for the mixed analysis of variance model. Biometrika, 54: 93-108.
  8. Kinderman, A.J. and J.F. Monathan, 1977. Computer generation of random variables using the ratio of normal deviates. Assoc. Comput. Math. Trans. Math. Soft., 3: 257-260.
  9. Efron, B., 1979. Bootstrap methods: Another look at the jackknife. Ann. Stat., 7: 1-26.
    CrossRefDirect Link
  10. Rao, C.R., 1971. Estimation of variance and covariance components MINQUE theory. J. Multi. Anal., 1: 257-275.
  11. Rao, C.R., 1971. Minimum variance quadratic unbiased estimation of variance components. J. Multi. Anal., 1: 445-456.
  12. Rao, C.R., 1972. Estimation of variance and covariance components in linear models. J. Multi. Anal., 67: 112-115.
  13. William, H.P., A. Saul, T. William and P. Brian, 1992. Numerical Recipes in C: The Art of Scientific Computing. Syndicate of the University of Cambridge, USA.
  14. Zhu, J. and B.S. Weir, 1994. Analysis of cytoplasmic and maternal effects: II. genetic model for triploid endosperm. Theor. Applied Genet., 89: 160-166.
  15. Zhu, J. and B.S. Weir, 1996. Diallel analysis for sex-linked and maternal effects. Theor. Applied Genet., 92: 1-9.
  16. Graybill, F.A. and A.W. Wortham, 1956. A note on uniformly best unbiased estimators for variance components. J. Am. Stat. Assoc., 51: 266-268.
  17. Zhu, J., 1997. Analysis Methods for Genetic Models (Chinese). Agricultural Publishing House of China, Beijing, pp: 295.

Search

Leave a Comment

Your email address will not be published. Required fields are marked *