Genomic selection in Gir cattle using female reference population

Author:

NAYEE NILESH,GAJJAR SWAPNIL,SUDHAKAR A,SAHA SUJIT,TRIVEDI KAMLESH,VATALIYA PRAVIN

Abstract

When a sizeable reference population of proven bulls is not available for implementing Genomic selection for a particular trait, and when a recording of certain traits on large scale is difficult, the use of a female reference population is recommended. Gir, one of the important milk purpose cattle breeds of India falls under this category. There is no large scale Progeny Testing (PT) programme in Gir, so proven bulls based on daughter performance in large numbers are not available. Considering the constraints, a genomic BLUP (GBLUP) model was implemented based on recorded cow reference population in Gir breed. Cows (3491) and 23 bulls were genotyped using INDUSCHIP for this purpose. Due to non-availability of pedigreed data, conventional breeding values (BV) of bulls and their reliabilities were not known. For comparison, assumed theoretical reliability of BV of a bull selected based on its dam's yield was compared with reliability obtained for genomic breeding value (GBV) using a GBLUP model. The reliability estimates for GBVs were 4 times higher than that for BVs. The predictive ability of the model was demonstrated by measuring the correlation between corrected phenotypes and GBVs for animals whose records were masked in a five-fold cross-validation study. The correlation was around 0.45 showing reasonable predictability of the GBLUP model. The GBVs were not biased. The regression coefficient between the corrected phenotype and GBV was 1.045. The present study demonstrates that it is feasible to implement genomic selection in Gir cattle in Indian conditions using a female reference population. It is expected that the bulls can be selected with around 4 fold more accuracy than the current method of selecting based on their dams' yield accelerating expected genetic growth in Gir cattle.

Publisher

Indian Council of Agricultural Research, Directorate of Knowledge Management in Agriculture

Subject

General Veterinary,Animal Science and Zoology

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