Indian Journal of Animal Research

  • Chief EditorK.M.L. Pathak

  • Print ISSN 0367-6722

  • Online ISSN 0976-0555

  • NAAS Rating 6.50

  • SJR 0.263

  • Impact Factor 0.4 (2024)

Frequency :
Monthly (January, February, March, April, May, June, July, August, September, October, November and December)
Indexing Services :
Science Citation Index Expanded, BIOSIS Preview, ISI Citation Index, Biological Abstracts, Scopus, AGRICOLA, Google Scholar, CrossRef, CAB Abstracting Journals, Chemical Abstracts, Indian Science Abstracts, EBSCO Indexing Services, Index Copernicus
Indian Journal of Animal Research, volume 53 issue 1 (january 2019) : 14-18

Genetic variability in exon 5 region of GH1 gene and its effect on milk production and milk composition traits in Karan Fries cattle

Aneet Kour, A.K. Chakravarty, T. Karuthadurai, Ekta Rana, Varinder Raina
1Animal Genetics and Breeding Division, ICAR- National Dairy Research Institute, Karnal- 132 001, Haryana, India
Cite article:- Kour Aneet, Chakravarty A.K., Karuthadurai T., Rana Ekta, Raina Varinder (2018). Genetic variability in exon 5 region of GH1 gene and its effect on milk production and milk composition traits in Karan Fries cattle. Indian Journal of Animal Research. 53(1): 14-18. doi: 10.18805/ijar.B-3461.
The study was conducted to identify the genetic variability in exon 5 region of GH1 gene and quantify its effect on production performance in Karan Fries cattle.PCR-RFLP method using Alu I restriction endonuclease was used for identification of genotypes. LL and LVgenotypes with frequencies as 0.46 and 0.54 and the frequency of L allele as 0.73 were found. Season of calving was only found significant (p £0.05) for fat yield of TD3, TD6 and TD10. The effect of SNP of GH1 gene (exon 5) increased the overall test day milk yield, fat yield and SNF yield by 1.05 kg, 43.2 gm and 103 gm.High correlations were obtained from TD3 onwards between test day traits and lactation milk yield indicating that selection based on identified SNP in TD3 increased test day milk yield, fat yield and SNF yield by 2.5229 kg, 62.9 gm and 215.9 gm, respectively.
  1. Anonymous (2012). 19thLivestock Census. Department of Animal Husbandry, Dairying and Fisheries, Ministry of Agriculture. Govt. of India.
  2. Anonymous (2015-16). Economic Survey 2015-16, Department of Economic Affairs, Ministry of Finance. Govt. of India.
  3. Falconer, D.S. and Mackay, T.F.C. (1996). Introduction to Quantitative Genetics. Longman Group Limited.
  4. Harvey, W.R. (1990). Users guide for LSMLMW and MIXMDL, PC2 version mixed model least squares and maximum likelihood computer programme, U.S.A. ARS.
  5. Khatami, S.R., Lazebny, O.E., Maksimenko, V.F. and Sulimova, G.E. (2005). Association of DNA polymorphisms of the growth hormone and prolactin genes with milk productivity in Yaroslavl and Black-and-White-cattle. Russian Journal of Genetics; 41(2):167-73.
  6. Sambrook, J. and Russel, D.W. (2001). Rapid isolation of yeast DNA. In: Molecular Cloning, a Laboratory Manual (Sambrook J and Russel DW, eds.). Cold Spring Harbor Laboratory, New York 631-632.
  7. Sarkar, U., Gupta, A.K., Sarkar, V., Mohanty, T.K., Raina, V.S. and Prasad, S. (2006). Factors affecting test day milk yield and milk composition in dairy animals. J. Dairying, Foods & H.S., 25(2): 129-132.
  8. Snedecor, G.W. and Cochran, W.G. (1994). Statistical Methods. Oxford & IBH Publ. Co., New Delhi, India.
  9. Tripathy, S.S. (2015).Genetic evaluation of Sahiwal and Karan Fries bulls for first lactation energy corrected milk production and productivity. M.V.Sc. Thesis. National Dairy Research Institute (Deemed University), Karnal, India.
  10. Wang, C.L., Ma. Pei-Pie, Zhang, Zhe, Ding, X.D., Liu, Jian-Feng, Fu, W.X., Weng, Z.Q and Zhang, Qin. (2011). Comparison of five methods for genomic breeding value estimation for the common dataset of the 15th QTL-MAS Workshop. 15th European workshop on QTL mapping and marker assisted selection (QTLMAS).

Editorial Board

View all (0)