Evaluation of Breeding Values and Variance Components of Birth and Weaning Weights in the Holstein Cows Herd Based on Genetic Information

Document Type : Original Articles

Authors

Department of Animal Production, College of Agricultural Engineering Sciences, University of Baghdad, Baghdad, Iraq

Abstract

Birth weights, weaning, and daily weight gain of calves before weaning vary according to farm animals' environment, production, and breeding systems. It is expected that these traits will be affected by direct genetic influences and the genetic effects of the mother. Therefore, this study was designed and conducted on 50 Holstein cows herds to estimate breeding value (after estimating the mean of allele effect and the mean of allele replacement effect of the DRB3 gene), as well as the variance components of the birth and weaning weight traits, depending on the variance resulting from the inherited polymorphism of the DBR3 gene. The results of this study showed a preference for the wild allele A based on its mutant counterpart B was the mean allele-effect value and the mean allele substitution value, corresponding to the preference for the A allele in both traits, the individuals with the AA genotype outperformed the homozygotes and mutants in the educational value (a value that is estimated based on what the individuals carry from the genotypes). The genetic variance of weaning weight was higher than the genetic variance of birth weight, and this may be due to the preference of allele A and the AA structure over the other two components in positively affecting birth and weaning weights, indicating the importance of this genetic structure of the DBR3 gene in selection within the genetic improvement programs for the color characteristic of Holstein cows.

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References

  1. Ma L, Brautbar A, Boerwinkle E, Sing CF, Clark AG, Keinan A. Knowledge-driven analysis identifies a gene–gene interaction affecting high-density lipoprotein cholesterol levels in multi-ethnic populations. PLoS Gen. 2012;8(5):e1002714.
  2. Lopes MS, Bastiaansen JW, Janss L, Knol EF, Bovenhuis H. Estimation of additive, dominance, and imprinting genetic variance using genomic data. Genes Genom Genet. 2015;5(12):2629-37.
  3. Jiang J, Shen B, O’Connell JR, VanRaden PM, Cole JB, Ma L. Dissection of additive, dominance, and imprinting effects for production and reproduction traits in Holstein cattle. BMC Genet. 2017;18(1):1-13.
  4. Moore T, Haig D. Genomic imprinting in mammalian development: a parental tug-of-war. Trends Genet. 1991;7(2):45-9.
  5. Wittenburg D, Melzer N, Reinsch N. Genomic additive and dominance variance of milk performance traits. J Anim Breed Genet. 2015;132(1):3-8.
  6. Xiang T, Christensen OF, Vitezica ZG, Legarra A. Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs. Genet Sel Evol. 2016;48(1):1-14.
  7. Pegolo S, Mota LFM, Bisutti V, Martinez-Castillero M, Giannuzzi D, Gallo L, et al. Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows. J Dairy Sci. 2021;104(10):10934-49.
  8. Amorena B, Stone W. Serologically defined (SD) locus in cattle. Science. 1978;201(4351):159-60.
  9. Pantelić V, Sretenović L, Ostojić-Andrić D, Trivunović S, Petrović MM, Aleksić S, et al. Heritability and genetic correlation of production and reproduction traits of Simmental cows. Afr J Biotechnol. 2011;10(36):7117-21.
  10. Spooner R, Levéziel H, Grosclaude F, Oliver R, Vaiman M. Evidence for a possible major histocompatibility complex (BLA) in cattle. Int J Immunogenet. 1978;5(5):335-46.
  11. Vandre R, Sharma A, Gowane G, Ravi R, Shweta R, Sinha R, et al. Polymorphism and disease resistance possessions of MHC class II BoLA genes. Double Helix Res-Int J Biomed Life Sci. 2014;5(2):362-72.
  12. Dibyendu C, Avtar S, Tantia M, Archana V, Chakravarty Genetic polymorphism of BoLA-DRB3. 2 locus in Sahiwal cattle. Anim Sci Report. 2015;9(1):33-40.
  13. Paswan C, Bhushan B, Patra B, Kumar P, Sharma A, Dandapat S, et al. Characterization of MHC DRB3. 2 alleles of crossbred cattle by polymerase chain reaction-restriction fragment length polymorphism. Asian-Australas J Anim Sci. 2005;18(9):1226-30.
  14. Calus MP. Genomic breeding value prediction: methods and procedures. Animal. 2010;4(2):157-64.
  15. Al-Waith K, AL-Anbari N, Mohamed T. Relationship of the DRB3 gen polymorphism with productive performance in Holstein cows. J Entomol Zool Stud. 2018;6(2):2363-6.
  16. Falconer DS. Early selection experiments. Annu Rev Genet. 1992;26(1):1-16.
  17. Schaeffer L. Strategy for applying genome‐wide selection in dairy cattle. J Anim Breed Genet. 2006;123(4):218-23.
  18. Visscher P, Woolliams J, Smith D, Williams J. Estimation of pedigree errors in the UK dairy population using microsatellite markers and the impact on selection. J Dairy Sci. 2002;85(9):2368-75.
  19. El-Saied U, De la Fuente L, Rodríguez R, San Primitivo F. Genetic parameter estimates for birth and weaning weights, pre-weaning daily weight gain and three type traits for Charolais beef cattle in Spain. Span J Agric Res. 2006;4(2):146-55.
  20. Falconer DS. Introduction to Quantitative Genetics: Pearson Education; 1996.
  21. Montaldo HH, López CT, Lizana C. Genetic parameters for milk yield and reproduction traits in the Chilean Dairy Overo Colorado cattle breed. Cienc Investig Agrar. 2017;44(1):24-34.
  22. Yaser ML, Senkal RH. Effect of mutation site of k-casein gene on protein quantity, composition, and other milk constituents in Holstein cows. J Pharm Sci Res. 2019;11(2):398-401.
  23. Behl JD, Verma N, Tyagi N, Mishra P, Behl R, Joshi B. The major histocompatibility complex in bovines: a review. Int Sch Res Notices. 2012;2012.
Archives of Razi Institute
Volume 77, Issue 5 - Serial Number 5
September and October 2022
Pages 1779-1783

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