Genetic analysis of production traits in Iranian Holstein cows considering genetic grouping

Document Type : Genetics & breeding

Authors

• Yahya Kheleghi fard ¹
• Mohammad Rokouei ¹
• Ahmad Moghimi Esfand Abadi ²
• Hadi Faraji-Arough ³

¹ Department of Animal Sciences, Faculty of Agriculture, Zabol University, Zabol, Iran

² Animal Breeding Center of Iran

³ Genetics and Animal Breeding, Research Center of special domestic animal, University of Zabol.

10.22067/ijasr.v12i3.76344

Abstract

Introduction: The lack of sufficient information in the pedigree of the animals prevents the correct estimation of the breeding values. Henderson proposed a genetic grouping for a more realistic estimation of breeding values for phenotypic records in different years. For these groups, the birth year, the year that the first daughter of the male had recorded, or the year that the male animal was used for insemination were used for grouping. In fact, this grouping was considered for calculating the genetic trend over the years. The incomplete recording of the animals in the population will result in the elimination of true genetic relationships between animals. Although, these animals are considered as the base animal in the analysis, but not born at the same time, and can affect the accuracy of estimated breeding values. The available pedigree information in Iran does not have a good quality index. So that the average of pedigree completeness criterion for Iranian Holstein cows has been reported less than 0.7. Genetic evaluation of Iranian Holstein cows with unknown parents may cause a bias in estimating genetic parameters and breeding values. The use of genetic groups in genetic analysis can partly correct the problem of animals with unknown parents. In this regard, the purpose of this study was to estimate the genetic parameters and breeding values of the production traits (milk, fat, protein) of Iranian Holstein cows with and without genetic grouping in model.
 
Materials and Methods: In this study, the pedigree of 1555702 heads of the Iranian Holstein cattle from 14623 sires and 697940 dams that collected by Animal breeding center of Iran till 2013, were used. Production traits, including milk, fat and protein corrected for 305 days and twice milking from first to third lactation periods were used to estimate variance components and breeding values. Herds under 100 heads were not considered for analysis and for all production traits; pedigree related to animals with the record was extracted from the general pedigree using CFC software  and used. For animals with unknown parents, genetic grouping was performed based on the sex and the birth year. Traits at different lactation periods analyzed with (model 2) and without (model 1) genetic grouping in the model and genetic trend was calculated. Then the accuracy of breeding values and genetic trend of traits obtained from different models were compared with each other. The Spearman rank correlation was used to investigate the change in animal ranking in a result of considering the genetic grouping.
 
Results and Discussion: The additive genetic variance and their standard error were lower for milk, fat and protein production traits in model with genetic grouping (model 21) than the model without genetic grouping (model 1). The estimated heritability range for milk, fat and protein production in three lactation periods with model 1 was 0.094-0.162, 0.069-0.114, and 0.079-0.123, respectively, that these values were higher than model 21 in terms of magnitude. Spearman rank correlation between the estimated breeding values with model 1 and 21 was significantly different from 1, indicating a change in animal rank with consideration of genetic grouping in the model. The spearman rank correlation was lower for males than females, suggesting a higher change in male animal's rank than females. The average accuracy estimated breeding values with model 21 was higher than model 1 and the average accuracy difference was significant between two models. The genetic trend in the first, second and third lactation periods with the model 21 was estimated 63.06, 59.60 and 44.64 for milk production, 1.346, 1.095 and 0.943 for fat and 1.542, 1. 514 and 1.035 kg per year for protein, which were higher than the estimates of model 1.
 
Conclusion: The results showed that consideration of genetic grouping in the model reduced the additive genetic variances of traits and the heritability estimated were higher without consideration of genetic grouping. The significance of the Spearman rank correlation indicates that the rank of males and females changed by inserting genetic groups into the model and change in the animal's rank for males was higher than females. The high accuracy of estimated breeding values and the genetic trends of traits in the model with genetic grouping suggests that genetic grouping for animals with unknown parents has been done and entered into the model in order to more accurately estimate the breeding values and to better reflect the performance of the breeding programs.

Keywords

• Genetic grouping
• Genetic trend
• Holstein
• Spearman correlation

20.1001.1.20083106.1399.12.3.7.8

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References

Butler, D. G., B. R. Cullis, A. R. Gilmour, and B. J. Gogel. 2009. ASReml-R reference manual. The State of Queensland, Department of Primary Industries and Fisheries, Brisbane. Available at http:// discoveryfoundation.org.uk/downloads/asreml/release3/asreml-R.pdf.

2- Cantet, R. J., L. R. Schaeffer, and C. Smith. 1992. Reduced animal model with differential genetic grouping for direct and maternal effects. Journal of Animal Science, 70(6):1730-1741.

3- Casellas, J., J. Piedrafta, and L. Varona. 2007. Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle. Genetic Selection Evolution, 39:39–53.

4- Da, Y., and M. Grossman. 1991. Multitrait animal model with genetic groups1. Journal of Dairy Science, 74(9):3183-3195.

5- Dahlin, A., U. N. Khan, A. H. Zafar, M. Saleem, M. A. Chaudhry, and J. Philipsson. 1998. Genetic and environmental causes of variation in milk production traits of Sahiwal cattle in Pakistan. Animal Science, 66(2): 307-318.

6- Famula, T., and L. Van Vleck. 1982. Monte Carlo study of genetic groups in sire evaluation. Journal of Dairy Science, 65:1286–1293.

7- Florence, P., and D. Lalon. 2004. Should genetic groups be fitted in BLUP evaluation? Practical answer for the French AI beef sire evaluation. Genetic Selection Evolution, 36(3):325-345.

8- Geldermann, H., U. Pieper, and W. E. Weber. 1986. Effect of misiden-tification on the estimation of breeding value and heritability in cattle. Journal of Animal Science, 63:1759–1768.

9- Golden, B. L., R. M. Bourdon, and W. M. Snelling. 1994. Additive genetic groups for animals evaluated in more than one breed association national cattle evaluation. Journal of Animal Science, 72(10):2559-2567.

10- Henderson, C. R. 1949. Estimation of changes in herd environment. Journal of Dairy Science, 32: 709 (Abstr).

11- Henderson, C. R. 1975a. Use of all relatives in intraherd prediction of breeding values and producing abilities. Journal of Dairy Science, 58(12):1910-1916.

12- Henderson, C. R. 1975b. Use of relationships among sires to increase accuracy of sire evaluation. Journal of Dairy Science, 58(11):1731-1738.

13- Hickey, J. M., M. G. Keane, D. A. Kenny, A. R. Cromie, and R. F. Veerkamp. 2007. Genetic parameters for EUROP carcass traits within different groups of cattle in Ireland. Journal of Animal Science, 85(2):314-321.

14- Hickey, J. M., M. G. Keane, D. A. Kenny, A. R. Cromie, H. A. Mulder, and R. F. Veerkamp. 2008. Estimation of accuracy and bias in genetic evaluations with genetic groups using sampling. Journal of Animal Science, 86(5):1047-1056.

15- Hosseinpour Mashhadi, M., M. R. Nassiri, N. Emam Jomeh Kashan, and R. Vaez Torshizi. 2007. Prediction breeding value and genetic parameter in Iranian Holstein bulls for milk production traits. Pakistan Journal of Biological Sciences, 11 (3): 108-112.

16- Jafari Torbaghan, M., H. Farhangfar, M. Bashtani, B. Mohammad Nazari, and H. Sarir. 2012. Genetic evaluation of cows for milk protein yield trait using fixed and random regression test day models. Animal Production Research, 1(2): 9-20.

17- Joaquim, C., J. Piedrafita, and L. Varona. 2007. Bayes factor for testing between different structures of random genetic groups: A case study using weaning weight in Bruna dels Pirineus beef cattle. Genetic Selection Evolution, 39(1):39-53.

18- Mosharraf, R., J. Shodja, M. Bohlouli, S. Alijani, and S. A. Rafat. 2014. Estimation of (co) variance components and breeding values for test-day milk production traits of Holstein dairy cattle via Bayesian approach. Biotechnology in Animal Husbandry, 30: (1): 15-28.

19- Mrode, R. A., and R. Thompson. 2005. Linear Models for the Prediction of Animal Breeding Values. 2^nd ed. CABI Pub.

20- Oliveira Júnior, G. A., J. P. Eler, J. B. S. Ferraz, J. Petrini, E. C. Mattos, and G. B. Mourão. 2013. Prediction of breeding values in beef cattle using different defnitions of additive genetic groups. Revista Brasileira de Saúde e Produção Animal, 14: 277–286.

21- Petrini, J., S. F. N. Pertile, J. P. Eler, J. B. S. Ferraz, E. C. Mattos, L. G. G. Figueiredo, and G. B. Mourão. 2015. Genetic grouping strategies in selection efficiency of composite beef cattle (Bos taurus× Bos indicus). Journal of Animal Science, 93(2): 541-552.

22- Phocas, F., and D. Laloë. 2004. Genetic parameters for birth and weaning traits in French specialized beef cattle breeds. Livestock Production Science, 89:121–128.

23- Piermati, C., and L. D. Van Vleck. 1993. Effect of genetic groups on estimates additive genetic variance. Journal of Animal Science, 71(1): 66-70.

24- Pollak, E. J., and R. L. Quaas. 1983. Definition of group effects in sire evaluation models. Journal of Dairy Science, 66(7):1503-1509.

25- Razm kabir, M., A. Nejati Javaremi, M. Moradi Shahr Babak, A. Rashidi, and M. Sayadnejad. 2009. Estimation of genetic trend for production traits of Holstein cattle in Iran. Iranian Journal of Animal Science, 40(1):7-11 [In Persian].

26- Robinson, G. K. 1986. Group effects and computing strategies for models for estimating breeding values. Journal of Dairy Science, 69(12):3106-3111.

27- Rokouei, M., R. Vaez Torshizi, M. Moradi Shahrbabak, M. Sargolzaei, and A. C. Srensen. 2010. Monitoring inbreeding trends and inbreeding depression for economically important traits of Holstein cattle in Iran. Journal of Dairy Science, 93(7): 3294-3302.

28- Saheb Honar, M.; M. Moradi Shahr Babak, S. R. Miraei Ashtiani, and M. Bagher Sayad Nezhad. 2010. An Estimation of genetic trend for production traits and a determination of the impact of some factors on it in Iranian Holstein cattle. Iranian Journal of Animal Science, 41(2):173-184 [In Persian].

29- Sargolzaei, M., H. Iwaisaki, and J. J. Colleau. 2006. CFC: A tool for monitoring geneic diversity. In 8^th World Congress on Geneics Applied to Livestock Producion, Belo Horizonte, Brazil.

30- Shiotsuki, L., F. F. Cardoso, J. A. Silva, and L. G. Albuquerque. 2013. Comparison of a genetic group and unknown paternity models for growth traits in Nellore cattle. Journal of Animal Science, 91(11):5135-5143.

31- Sullivan, P. 1995. Alternatives for genetic evaluation with uncertain parentage. Canadian Journal of Animal  Science, 75:31–36.

32- Theron, H., F. Kanfer, and L. Rautenbach. 2002. The effect of phantom parent groups on genetic trend estimation. South African Journal of Animal Science, 32:130–135.

33- Van der Werf, J. H., and I. J. de Boer. 1990. Estimation of additive genetic variance when base populations are selected. Journal of Animal Science, 68(10): 3124-3132.

34- Visscher, P. M., and R. Thompson. 1992. Univariate and multivariate parameter estimates for milk production traits using an animal model. I. Description and results of REML analyses. Genetics Selection Evolution, 24(5): 415 (Abstr).

35- Weller, J. I., and E. Ezra. 2004. Genetic analysis of the Israeli Holstein dairy cattle population for production and nonproduction traits with a multitrait animal model. Journal of Dairy Science, 87(5): 1519-1527.

36- Westell, R. A., R. L. Quaas, and L. D. Van Vleck. 1988. Genetic groups in an animal model. Journal of Dairy Science, 71(5):1310-1318.

37- Yaeghoobi, R., A. Doosti, A. M. Noorian, and A. M. Bahrami. 2011. Genetic parameters and trends of milk and fat yield in Holstein^, s dairy cattle of West provinces of Iran. International Journal of Dairy Science, 6: 142-149.