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Association of prolactin gene polymorphism with milk production traits in Gaolao cattle

*D. S. Kale  -  Department of Animal Genetics and Breeding, Nagpur Veterinary College,, India
J. Singh  -  Department of Animal Genetics and Breeding, Nagpur Veterinary College,, India
Y. B. Sathe  -  Department of Animal Genetics and Breeding, Nagpur Veterinary College,, India
A. Wankhade  -  Department of Animal Genetics and Breeding, Nagpur Veterinary College,, India
P. D. Dudule  -  Department of Animal Genetics and Breeding, Nagpur Veterinary College,, India
D. V. Patil  -  Department of Animal Genetics and Breeding, Nagpur Veterinary College,, India
G. R. Gowane  -  Department of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, India
Open Access Copyright (c) 2024 Journal of the Indonesian Tropical Animal Agriculture
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Abstract
The present study aimed to identify the DNA polymorphisms within prolactin gene regions of Gaolao cattle and to investigate their relation with milk production traits. The genomic DNA was isolated from 245 unrelated animals of Gaolao cows, and test-day milk traits data were recorded. PCRRFLP, PCR-SSCP and direct sequencing methods for mutation confirmation were used to study polymorphism within the prolactin gene. The PCR-RFLP genotyping at the exon-3 region of the prolactin gene revealed polymorphism and found an association of the PRLG1-RsaI ‘AA’ genotype with milk yield (5.05±0.14*) in Gaolao cattle. The exon-4, intron-3,4, Exon-5, 5'flanking, and exon-1 regions of prolactin revealed SSCP polymorphisms and SNPs. The results of the study indicate the existence of a substantial amount of genetic variation within the above-studied regions of the prolactin candidate gene. The identified association at PRLG1-RsaI genotype with milk yield will aid in future geneassisted selection and improvement strategies in Gaolao indigenous cattle.

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Keywords: DNA marker; Milk production traits; Prolactin; Zebu cattle
Funding: Science and Engineering Research Board-Department of Science and Technology, New Delhi, India under Core Research Grant Scheme (File No. EMR/2017/000323)

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