Skip to main content
Log in

Genetic evaluation of growth in Barki sheep using random regression models

  • Regular Articles
  • Published:
Tropical Animal Health and Production Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • 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, 689–700

    Google Scholar 

  • Abou Khadiga, G.A., Mahmoud, B.Y.F., Farahat, G.S. and Emam, A.M., 2015. Genetic analysis of partial egg production records in Japanese quail using random regression models. Poultry Science. 96: 2569–2575. doi: https://doi.org/10.3382/ps/pex081

    Article  Google Scholar 

  • Agudelo-Gómez DA, Savegnano RP, Buzanskas ME and Ferraudo AS, Munari DP, Cerón-Muñoz M, 2015. Genetic principal components for reproductive and production traits in dualpurpose buffaloes in Colombia. Journal of Animal Science, 93, 3801–3809

    Article  PubMed  Google Scholar 

  • Akaike, H., 1974. A new look at the statistical model identification. IEEE Trans. Automat. Control, 19, 716–723

    Article  Google Scholar 

  • Elshennawy, M., 1995. Sheep development program in Egypt 32, 27–32

    Google 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, 783–789

    Google Scholar 

  • FAOSTAT, 2016. URL http://www.fao.org/faostat/en/#data. Accessed on May, 2018.

  • Farzin, N., Torshizi, R.V., Gerami, A. and Seraj, A., 2013. Estimates of genetic parameters for monthly egg production in a commercial female broiler line using random regression models. Livestock Science, 153, 33–38

    Article  Google Scholar 

  • Fischer, T. Van der Werf, JHJ, Banks, R., Ball, A. and Gilmour, A.R., 2006. Genetic analysis of weight , fat and muscle depth in growing lambs using random regression models. Journal of Animal Science, 82, 13–22

    Article  Google Scholar 

  • Ghafouri-Kesbi, F. and Baneh, H., 2012. Genetic parameters for direct and maternal effects on growth traits of sheep Archiv Tierzucht, 55, 603–611

    Google 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, 235–246

    Google 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, 979–993

    CAS  PubMed  PubMed Central  Google 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, 470–475

    Google Scholar 

  • Legarra A., Misztal I, Bertrand J, 2004. Constructing covariance functions for random regression models for growth in Gelbvieh beef cattle. Journal of Animal Science, 82, 1564–1571

    Article  CAS  PubMed  Google 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, 567–576

    Google Scholar 

  • Mandal, A., Pant, K.P., Nandy, D.K., Rout, P.K. and Roy, R., 2003. Genetic Analysis of Growth Traits in Muzafarnagari sheep. Tropical Animal Health and Production. 35, 271–284

    Article  CAS  PubMed  Google Scholar 

  • Mandal, A., Dass, G. and Rout, P.K., 2012. Model comparisons for estimation of genetic parameters of pre-weaning daily weight gains in Muzaffarnagari sheepSmall Ruminant Research, 106, 118–124

    Article  Google Scholar 

  • Meyer, K., 2004. Scope for a random regression model in genetic evaluation of beef cattle for growth. Livestock Production Science, 86, 69–83

    Article  Google Scholar 

  • Meyer, K., 2007. WOMBAT---A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML) Journal of Zhejiang University SCIENCE B, 8, 815–821

    Article  PubMed  PubMed Central  Google 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, 2830–2839

    Google 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, 57–69

  • Naderi, Y. 2018. Genetic evaluation and genetic trend of growth in makouei sheep via random regression. The Journal of Animal & Plant sciences. 28 (2), 388–395

    Google 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.

  • 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, 1–12

  • 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 .

    Article  Google 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, 19–28

    Google 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, 94-100

  • 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,

  • Sarmento, L. R., Torres, R.D.A., De Sousa, W.H., De Albuquerque, L.G., Lobo, R.N. and De Sousa, J.E. 2011. Modeling of average growth curve in Santa Ines sheep using random regression models. R. Bras. Zootec, 40. 314–322

    Article  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

    Article  Google Scholar 

  • Schaeffer, L.R., 2004. Application of random regression models in animal breeding Livestock Production Science, 86, 35–45

    Article  Google Scholar 

  • Schaeffer, L.R. 2016. Random Regression Models. Lectures notes. University of Guelf, Canda, 1–164.

    Google Scholar 

  • Schwarz, G., 1978. Estimating the dimension of a model. Anual statistics, 6, 461–464

    Article  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, 44–49

    Google Scholar 

  • Venkataramanan, R., 2016. Random regressions to model growth in Nilagiri sheep of South India. Small Ruminant Research, 144, 242–247.

    Article  Google Scholar 

  • Wolc, A., Barczak, E., Wójtowskic, J., Slósarz, P., Szwaczkowski T., 2011. Genetic parameters of body weight in sheep estimated via random regression and multi-trait animal models. Small Ruminant Research, 100, 15–18.

    Article  Google 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, 647–654

    Google Scholar 

Download references

Acknowledgements

The authors are acknowledging the Department of Animal Breeding and Genetic, DRC, for providing the dataset. Recommendations from Dr. Galal Abou Khadiga are appreciated.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmed M. Sallam.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interests.

Ethical standards

The manuscript does not contain clinical studies or patient data.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sallam, A.M., Ibrahim, A.H. & Alsheikh, S.M. Genetic evaluation of growth in Barki sheep using random regression models. Trop Anim Health Prod 51, 1893–1901 (2019). https://doi.org/10.1007/s11250-019-01885-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11250-019-01885-3

Keywords

Navigation