Genomic selection of Nili-Ravi buffalo: A choice for buffalo breeders

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M. Moaeen-ud-Din G. Bilal


Among three well documented breeds of buffalo dairy breeds in Pakistan, Nili-Ravi is the best milk producer owing to its characteristic of disease and parasitic resistance, and better convertor of roughages into useful products than cattle. A selection program to enhance the genetic potential for milk production of Nili-Ravi using progeny testing program is going on. Traditional progeny testing program has made a remarkable improvement in the genetic potential of dairy cattle in the developed world. However, this program faces severe implementation issues in buffalo improvement due to limitation of resources and basic infrastructure. Simulated studies have shown the potential of genomic selection in shortening generation interval and increasing the accuracy of selection (especially young bulls) that can bring a relatively rapid genetic improvement. The current study intends to explore the application of genomic selection in a typical buffalo breeding perspective using Nili-Ravi in Pakistan as an example. The assumed size of the training population for genomic selection was 15860 present with BRI, Pattoki. Our calculations indicated that genomic selection can reduce the generation intervals in the male to male selection pathway from 9.5 years down to 3.3 years. It can result in almost 2 times increase in response to selection compared to that in a progeny testing program. Furthermore, it reduced the costs of proving bulls by 88%. The present study suggests the initiation of the program of genomic selection for Nili-Ravi in Pakistan and may serve as an example for other developing countries. The findings of the current study may encourage the researchers and policy makers to use the genomic selection for improvement in the productivity of dairy buffalo of developing countries.

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MOAEEN-UD-DIN, M.; BILAL, G.. Genomic selection of Nili-Ravi buffalo: A choice for buffalo breeders. Buffalo Bulletin, [S.l.], v. 35, n. 4, p. 595-606, dec. 2016. ISSN 2539-5696. Available at: <>. Date accessed: 17 sep. 2021.
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