The study of possibility of genetic selection in order to increase the uniformity of body weight in Japanese quail

Document Type : Research Paper


1 Assistant Professor, Faculty of Agricultural Science, Payame Noor University, Tehran, Iran

2 Assistant Professor, Faculty of Agricultural and natural resources, Lorestan University, Khorram-Abad, Iran


The aim of this research was to estimate genetic parameters for mean and residual of body weight in Japanese quail. A total of 2629 quail body weight records at 28 days old were used in this research. Double hierarchical generalized linear model (DHGLM) was used to estimate (co) variance components using ASREML 4.0 software. Additive genetic variance for mean and residual were 189.59 and 0.18, respectively and were statistically significant (p<0.01). The genetic standard deviation for residual of body weight was 0.42. Therefore decreasing estimated breeding value of residual by 1 genetic standard deviation can increase the uniformity of body weight at 28 days old by 42%. Heritability for mean (0.51) was larger than the heritability for the residual (0.02). Although heritability for residual was low but it was significant (p<0.01). The Spearman rank correlation between estimated breeding values in mean and dispersion was low (0.094). Low and unfavorable genetic correlation (0.09) was obtained between mean and residual. The results obtained in this research show the residual of body weight records at 28 days old is under control of additive genetic variance and uniformity can be achieved by means of genetic selection.


  1. Bodin, L., Garcia, M., Saleil, G., Bolet, G. & Garreau, H. (2010). Results of 10 generations of canalising selectionfor rabbit birth weight. In: 9th World Congress on genetics applied to livestock production (p. 1-4), Leipzig, Germany.
  2. Felleki, M., Lee, D., Lee, Y., Gilmour, A. R. & Rönnegård, L. (2012). Estimation of breeding values for mean and dispersion, their variance and correlation using double hierarchical generalized linear models. Genetics research, 94, 307-317.
  3. Garreau, H., Bolet, G., Larzul, C., Robert-Granie, C., Saleil, G., SanCristobal, M. & Bodin, L. (2008). Results of four generations of a canalising selection for rabbit birth weight. Livestock Science, 119, 55-62.
  4. Ghiasi, H. & Felleki, M. (2016). Joint estimation of (co) variance components and breeding values for mean and dispersion of days from calving to first service in Holstein cow. Animal Production Science, 57, 760-766.
  5. Gilmour, A. R., Gogel, B. J., Cullis, B. R., Welham, S. J. & Thompson, R. (2014). ASReml User Guide Release 4.VSN International Ltd, Hemel Hempstead, HP1 1ES, UK. Available from:
  6. Gutiérrez, J. P., Nieto, B., Piqueras, P., Ibáñez, N. & Salgado, C. (2006). Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genetics Selection Evolution, 38, 445.
  7. Hohenboken, W. D. (1985). The manipulation of variation in quantitative traits: a review of possible genetic strategies. Journal of Animal Science, 60, 101-110.
  8. Morante, R., Goyache, F., Burgos, A., Cervantes, I., Pérez-Cabal, M. A. & Gutiérrez, J. P. (2009). Genetic improvement for alpaca fibre production in the Peruvian Altiplano: the Pacomarca experience. Animal Genetic Resources, 45, 37-43.
  9. Mulder, H. A., Hill, W. G., Vereijken, A. & Veerkamp, R. F. (2009). Estimation of genetic variation in residual variance in female and male broiler chickens. Animal, 3, 1673-1680.
  10. Mulder, H. A., Bijma, P. & Hill, W. G. (2008). Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance. Genetics Selection Evolution, 40, 37-60.
  11. Mulder, H. A., Bijma, P. & Hill, W. G. (2007). Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance. Genetics, 175, 1895-1910.
  12. Neves, H. H. R., Carvalheiro, R., Roso, V. M. & Queiroz, S. A. (2011). Genetic variability of residual variance of production traits in Nellore beef cattle. Livestock Science, 142, 164-169.
  13. Rönnegård, L., Felleki, M., Fikse, W. F., Mulder, H. A. & Strandberg, E. (2013). Variance component and breeding value estimation for genetic heterogeneity of residual variance in Swedish Holstein dairy cattle. Journal of dairy science, 96, 2627-2636.
  14. Rönnegård, L., Felleki, M., Fikse, F., Mulder, H. A. & Strandberg, E. (2010). Genetic heterogeneity of residual variance-estimation of variance components using double hierarchical generalized linear models. Genetics Selection Evolution, 42, 8-17.
  15. Sørensen, P., de los Campos, G., Morgante, F., Mackay, T. F. & Sorensen, D. (2015). Genetic control of environmental variation of two quantitative traits of Drosophila melanogaster revealed by whole-genome sequencing. Genetics, 201, 487-497.