Genetic evaluation of growth in Barki sheep using random regression models
- 44 Downloads
The objective of the current study was to estimate covariance components of growth at different ages from birth to yearling in Barki lambs. A total of 16,496 records for body weights at birth (W0), 3 (W3), 6 (W6), 9 (W9), and 12 (12) months of age for Barki lambs were available. Two statistical approaches were used; multi-trait (MT) and random regression (RR) animal models assuming two random effects only, additive genetic effect (σ2a) and permanent environmental effect (σ2pe) of the animal. Regarding the RR model, Legendre polynomials (LP) of different orders for the random parts were compared in order to evaluate the most appropriate model. Bayesian information and Akaike information criteria suggested that the optimal RR model included the third order for fixed effect of lamb age and σ2pe, and fourth order of LP for σ2a (LP343). Estimates of direct heritability (h2a) from LP343 showed an ascending pattern, as it was 0.06 ± 0.03 for birth weight and reached to the peak at 9 months (0.42 ± 0.02). Thereafter, it declined again at the end of trajectory (12 months of age; 0.27 ± 0.03). The MT model showed a fluctuated pattern and lower estimates of h2a (0.19 ± 0.03, 0.11 ± 0.02, 0.12 ± 0.02, 0.11 ± 0.03, and 0.16 ± 0.04 for W0, W3, W6, W9, and W12, respectively). Considerably, similar ascending patterns of the ratio of σ2pe to phenotypic variance were reported from both RR (from 3 to 50%) and MT models (from 5 to 20%). Of interest, the RR model showed higher predicting ability of the breeding values compared with the MT model, which is an indicator for the suitability of RR models for analyzing the consecutive growth traits in sheep. Results suggested that the Barki sheep has a potential for genetic selection based on weight at different ages with selection likely to be more efficient at 9 months of age.
KeywordsGenetic parameters Body weight Sheep
The authors are acknowledging the Department of Animal Breeding and Genetic, DRC, for providing the dataset. Recommendations from Dr. Galal Abou Khadiga are appreciated.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interests.
The manuscript does not contain clinical studies or patient data.
- Abegaz, S., Wyk, J.B.V.A.N. and Olivier, J.J., 2010. Estimates of ( co )variance function for growth to yearling in Horro sheep of Ethiopia using random regression model. Archiv Tierzucht. 53, 689–700Google Scholar
- Elshennawy, M., 1995. Sheep development program in Egypt 32, 27–32Google Scholar
- El-wakil, S.I., 2013. Estimates of genetic parameters of early growth traits of barki sheep of Egypt. Egyptian Journal of Animal Production. 4, 783–789Google Scholar
- FAOSTAT, 2016. URL http://www.fao.org/faostat/en/#data. Accessed on May, 2018.
- Ghafouri-Kesbi, F. and Baneh, H., 2012. Genetic parameters for direct and maternal effects on growth traits of sheep Archiv Tierzucht, 55, 603–611Google Scholar
- Ghafouri-Kesbi, F.G., Eskandarinasab, M. and Shahir, M.H., 2008. Estimation of direct and maternal effects on body weight in Mehraban sheep using random regression models, Archiv Tierzucht. 51, 235–246Google Scholar
- Jannoune, A., Boujenane, I., Falaki, M. and Derqaoui, L., 2015. Genetic analysis of live weight of Sardi sheep using random regression and multi-trait animal models , Small Ruminant Research, doi: https://doi.org/10.1016/j.smallrumres.2015.06.015
- Kirkpatrick M, Lofsvold D, Bulmer M., 1990. Analysis of the inheritance, selection and evolution of growth trajectories. Genetics, 124, 979–993Google Scholar
- Kranis, A., Su, G., Sorensen, D. and Woolliams, J.A., 2004. The Application of Random Regression Models in the Genetic Analysis of Monthly Egg Production in Turkeys and a Comparison with Alternative Longitudinal Models. Poultry Science, 86, 470–475Google Scholar
- Malhado C, Malhado A, Ramos A, Carneiro P, F Siewerdt, A Pala 2012. Genetic parameters by bayesian inference for dual purpose Jaffarabadi buffaloes Archiv Tierzucht, 55, 567–576Google Scholar
- Mohammadi, A. and Farhadian, M., 2017. Genetic evaluation of growth traits in Iranian Kordi Sheep using random regression model with homogeneous and heterogeneous residual variances , Genetika, doi: https://doi.org/10.2298/GENSR1702469M
- Molina, A., Mene’ndez-Buxadera, A., Valera, M. and Serradilla, J.M., 2014. Random regression model of growth during the first three months of age in Spanish Merino sheep. Journal of Animal Sciences. 85, 2830–2839Google Scholar
- Mousa, E., M. Osman and U. ElSaied 2006. Genetic parameters for body weight of lambs with random regression models. Egyptian Journal of Animal Production, 43, 57–69Google Scholar
- Naderi, Y. 2018. Genetic evaluation and genetic trend of growth in makouei sheep via random regression. The Journal of Animal & Plant sciences. 28 (2), 388–395Google Scholar
- Nemutandani, K., Snyman, G., Olivier, W. and Visser, C., 2018. Estimation of variance components and heritabilities for body weight from birth to six years of age in Merino sheep using random regression models. Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.215.Google Scholar
- Ning, C., Kang, H., Zhou, L., Wang, D., Wang, H., Wang, A. and Fu, J., 2017. Performance Gains in Genome- Wide Association Studies for Longitudinal Traits via Modeling Time-varied effects. Scientific Reports, 1–12Google Scholar
- Saghi, D., Reza, A., Kazemi, F. and Mohammadi, K., 2018. Estimates of covariance functions for growth of Kordi sheep in Iran using random regression models Estimates of covariance functions for growth of Kordi sheep in Iran using random regression models Small Ruminant Research, 162, 69–76 .CrossRefGoogle Scholar
- Sallam, A.M., Galal, S., Rashed, M.A. and Alsheikh, S.M., 2012. Genetic diversity in barki sheep breed in its native tract in Egypt, Egyptian Journal of Animal Production, 49, 19–28Google Scholar
- Sallam, A.M., Ibrahim, A. and Alsheikh, S.M., 2019. Estimation of genetic parameters and variance components of pre-weaning growth traits in Barki lambs. Small Ruminant Research, 173, 94-100Google Scholar
- Sargolzaei, M., Iwaisaki, H. and Colleau, J.J., 2006. CFC: A tool for monitoring genetic diversity, Proceedings of the World Congress on Genetics Applied to Livestock Production,Google Scholar
- Sarti, F.M., Lasagna, E., Giontella, A., Panella, F., Sarti, F.M., Lasagna, E., Giontella, A., Panella, F., Pieramati, C., Agrarie, S. and Veterinaria, M., 2016. The Use of a Random Regression Model on the Estimation of Genetic Parameters for Weight at Performance Test in Appenninica Sheep Breed , Italian Journal of Animal Science, 14:3, 3892, doi: https://doi.org/10.4081/ijas.2015.3892 CrossRefGoogle Scholar
- Schaeffer, L.R. 2016. Random Regression Models. Lectures notes. University of Guelf, Canda, 1–164.Google Scholar
- Vatankhah, M., 2013. Genetic analysis of ewe body weight in Lori-Bakhtiari sheep using random regression models. Journal of Livestock Science and Technologies. 1, 44–49Google Scholar
- Zamani, P., Moradi, M.R., Alipour, D. and Ahmadi, A., 2015. Estimation of Variance Components for Body Weight of Moghani Sheep Using B - Spline Random Regression Models. Iranian Journal of Applied Animal Science, 5, 647–654Google Scholar