The maintenance of genetic diversity in a local cattle breed through optimal contribution selection

Nadia Guzzo, Cristina Sartori, Enrico Mancin, Roberto Mantovani


Submitted 2020-07-24 | Accepted 2020-09-09 | Available 2020-12-01

The present study aimed to evaluate the effects of optimum contribution selection (OCS) in a small native cattle breed. In practical animal breeding, the genetic improvement is often accompanied by an increase of inbreeding level due to the preferential use of closely related animals, particularly in small populations. This may lead to a reduction of genetic variability and to detrimental effects on some traits. The OCS maximizes the genetic merit of newborns while putting a restriction on the average relationship of the current generation. Despite the benefits, OCS has not been widely applied in practical breeding plans yet. This study considered the effects of OCS in the dual-purpose Rendena cattle, by applying different penalties to the average relationship of current generation (from 0 to -100,000). The OCS was applied on the candidate bull-dams and bull-sires for the years 2014 to 2019, and compared with simulations of random mating, traditional selection and mating system used by the breeders association. Considering the mating of 2014 and 2015, OCS allowed to obtain a predicted offspring with lower genetic merit than in traditional selection, but also with a lower inbreeding. When OCS was routinely introduced in the breed, in 2016, a reduction in genetic merit but also a consistent reduction in the average relatedness and inbreeding rate were observed. Subsequent years showed the actual effects of the OCS program: after the introduction of the optimization, the inbreeding rate did not increase over years. Moreover, the traditional mating system results were suboptimal in respect to OCS simulations. The study confirmed the benefit of OCS as effective tool for long-term preservation of small local breeds under selection, which is important for biodiversity and sustainable use of the genetic resources.

Keywords: optimal contribution selection, native cattle, small population, inbreeding, Rendena


Berg, P., Nielsen, J. and Sørensen, M. K. (2006). EVA: Realized and predicted optimal genetic contributions. In Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006 (pp. 27-09).

Biscarini, F. et al. (2015). Challenges and opportunities in genetic improvement of local livestock breeds. Frontiers in Genetics, 6, 33.

Clark, S. A. et al. (2013). The effect of genomic information on optimal contribution selection in livestock breeding programs. Genetics Selection Evolution, 45(1), 44.

Gandini, G. et al. (2014). Selection with inbreeding control in simulated young bull schemes for local dairy cattle breeds. Journal of Dairy Science, 97(3), 1790-1798.

Gorjanc, G. and Hickey, J. M. (2018). AlphaMate: a program for optimizing selection, maintenance of diversity and mate allocation in breeding programs. Bioinformatics, 34(19), 3408-3411.

Gourdine, J. L., Sørensen A. C. and Rydhmer, L. (2012). There is room for selection in a small local pig breed when using optimum contribution selection: a simulation study. Journal of Animal Science, 90(1), 76-84.

Guzzo, N., Sartori, C. and Mantovani, R. (2018). Heterogeneity of variance for milk, fat and protein yield in small cattle populations: The Rendena breed as a case study. Livestock Science, 213, 54-60.

Hasler, H. et al. (2011). Genetic diversity in an indigenous horse breed–implications for mating strategies and the control of future inbreeding. Journal of Animal Breeding and Genetics, 128(5), 394-406.

Henryon, M. et al. (2015). Most of the long-term genetic gain from optimum-contribution selection can be realised with restrictions imposed during optimisation. Genetics Selection Evolution, 47(1), 21.

Kjetså, M. H. (2016). Optimal Contribution Selection Applied to the Norwegian Cheviot Sheep Population. Master's thesis, Norwegian University of Life Sciences, Ås, 2016.

Kettunen, A. and Berg, P. (2017). Faroese Horse: Population status & conservation possibilities. urn:nbn:se:norden:org:diva-5822

Kohl, S., Wellmann, R. and Herold, P. (2020). Advanced optimum contribution selection as a tool to improve regional cattle breeds: a feasibility study for Vorderwald cattle. Animal, 14(1), 1-12.

Leroy, G. (2014). Inbreeding depression in livestock species: review and meta‐analysis. Animal Genetics, 45(5), 618-628.

Meuwissen, T. H. E. (1997). Maximizing the response of selection with a predefined rate of inbreeding. Journal of Animal Science, 75(4), 934-940.

Meuwissen, T. H. E. and Luo, Z. (1992). Computing inbreeding coefficients in large populations. Genetics Selection Evolution, 24(4), 1-9.

Mwangi, S. I. et al. (2020). Effect of controlling future rate of inbreeding on expected genetic gain and genetic variability in small livestock populations. Animal Production Science.

Olsen, H. F., Meuwissen, T. and Klemetsdal, G. (2013). Optimal contribution selection applied to the Norwegian and the North‐Swedish cold‐blooded trotter–a feasibility study. Journal of Animal Breeding and Genetics, 130(3), 170-177.

Sartori, C. et al. (2018). Genetic correlations among milk yield, morphology, performance test traits and somatic cells in dual-purpose Rendena breed. Animal, 12(5), 906-914.

Solé, M. et al. (2013). Implementation of Optimum Contributions Selection in endangered local breeds: the case of the Menorca Horse population. Journal of Animal Breeding and Genetics, 130(3), 218-226.

Sonesson, A. K. and Meuwissen, T. H. (2000). Mating schemes for optimum contribution selection with constrained rates of inbreeding. Genetics Selection Evolution, 32(3), 231-248.

Sørensen, M. K. et al. (2008). Optimal genetic contribution selection in Danish Holstein depends on pedigree quality. Livestock Science, 118(3), 212-222.

Wang, Y., Bennewitz, J. and Wellmann, R. (2017). Novel optimum contribution selection methods accounting for conflicting objectives in breeding programs for livestock breeds with historical migration. Genetics Selection Evolution, 49(1), 45.

Wellmann, R., Hartwig, S. and Bennewitz, J. (2012). Optimum contribution selection for conserved populations with historic migration. Genetics Selection Evolution, 44(1), 34.

Wray, N. R. and Goddard, M. E. (1994). Increasing long-term response to selection. Genetics Selection Evolution, 26(5), 1-21.

Full Text:



  • There are currently no refbacks.

Copyright (c) 2020 Acta Fytotechnica et Zootechnica

© Slovak University of Agriculture in Nitra, Faculty of Agrobiology and Food Resources