Animal Bioscience

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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Composite genotypes of progestogen-associated endometrial protein gene and their association with composition and quality of dairy cattle milk

  • Kolenda, Magdalena (Department of Animal Biotechnology and Genetics, Faculty of Animal Breeding and Biology, UTP University of Science and Technology) ;
  • Sitkowska, Beata (Department of Animal Biotechnology and Genetics, Faculty of Animal Breeding and Biology, UTP University of Science and Technology) ;
  • Kamola, Dariusz (Department of Physiological Sciences, Faculty of Veterinary Medicine, Warsaw University of Life Sciences) ;
  • Lambert, Barry D. (Department of Animal Science and Veterinary Technology, Tarleton State University)
  • Received : 2020.08.26
  • Accepted : 2021.02.02
  • Published : 2021.08.01
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Abstract

Objective: The progestogen-associated endometrial protein (PAEP) gene encodes the main whey protein in milk, β-lactoglobulin. The aim of the study was to investigate polymorphism in the PAEP gene and its association with milk yield, composition, and quality. Methods: Test-day records for 782 dairy cows were analysed. A total of 10 single nucleotide polymorphisms (SNP) within the PAEP gene were investigated. The following parameters were recorded: milk yield (MY, kg/d), percent milk fat (%), protein (PP, %), dry matter (DMP, %) and lactose (LP, %), urea content (UC, mg/L) as well as natural logarithm for somatic cell count (LnSCC, ln). Effect on genomic estimated breeding values accuracy was evaluated with pedigree and single step model. Results: Results show that only three SNPs were polymorphic, creating 5 composite genotypes: P1 to P5. Differences in MY between composite genotypes were noted in the two tested herds. Cows with P5 composite genotypes were characterised by the highest PP and LnSCC and the lowest LP and UC (p<0.05). P4 was linked to an increased DMP and UC, while P3 to an increase in LP and decrease in PP and LnSCC. Both factors are important markers in herd management and have high influences on the herds economics. For 5 out of 7 traits the accuracy of prediction was improved by including the haplotype as a fixed effect. Conclusion: Presented results may suggest a new way to optimise breeding programmes and demonstrate the impact of using genomic data during that process.

Keywords

Acknowledgement

This article has been supported by the Polish National Agency for Academic Exchange under Grant No. PPI/APM/2019/1/00003 as well as by the Ministry of Science and Higher Education of the Republic of Poland (funds for statutory activity BN-51/2019)

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