Relationship between Kappa-Casein gene polymorphism with milk economic traits in native cattle of Guilan province

Document Type : Research Paper

Authors

1 MSc. Student, Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

2 Professor, Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

3 Associate Professor, Department of Animal Science, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran

4 Scientific board member of Animal Science Research Department, Guilan Agricultural and Natural Resources Research and Education Center, Rasht, Iran

5 Senior expert, Animal Production Improvement Assistant, Jihad-e-Keshavarzi Organization of Guilan, Rasht, Iran

Abstract

In this research, the relationship between polymorphism of CSN (Kappa-Casein) gene and production traits in Guilan native cattle was studied. Blood samples were taken from 100 cows Fouman, Rasht and Astaneh-ye-Ashrafiyeh. Genomic DNA was extracted by modified salting out method. A 350 bp fragment of the bovine kappa-CSN gene was amplified by Polymerase Chain Reaction (PCR) using a specific primer. The PCR products were digested by Hinf I to determine kappa-casein genotypes with PCR-RFLP marker. Observed frequencies for genotypes AA, AB, BB were 0.48, 0.52, 0.00 and allelic frequencies for A and B were 0.74 and 0.26, respectively. The chi-square test results showed that the studied population were not at Hardy-Weinberg equilibrium. Comparison of least square means indicated that the polymorphism has a significant effect on milk yield, fat and protein percentage (P<0.01). The cows with genotype AA produced 0.81 kg more milk over the cows with genotype AB. The cows with genotype AB produced 0.1 and 0.14 percentages higher milk fat content compare to the cattle with genotypes of AA (P<0.01). The results also revealed that the cattle with genotypes of AA produced milk with lowest fat and protein content.

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Main Subjects

References

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Animal Production Research
Volume 6, Issue 1
June 2017
Pages 53-61

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