Wydanie 366(65)1 2023

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http://hdl.handle.net/20.500.12539/1932

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Przeglądaj Wydanie 366(65)1 2023 wg Autor "Czerniawska-Piątkowska, Ewa"

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    Effect of polymorphisms in exon 8 of the PPARGC1A gene on milk production traits in cattle
    (Wydawnictwo Uczelniane Zachodniopomorskiego Uniwersytetu Technologicznego w Szczecinie, 2023) Śpiewak, Magdalena; Kowalewska, Inga; Czerniawska-Piątkowska, Ewa; Department of Genetics, Faculty of Biotechnology and Animal Breeding, West Pomeranian University of Technology, Szczecin, Poland; Department of Genetics, Faculty of Biotechnology and Animal Breeding, West Pomeranian University of Technology, Szczecin, Poland; Department of Ruminant Science, Faculty of Biotechnology and Animal Breeding, West Pomeranian University of Technology, Szczecin, Poland
    The objective of this study was to investigate associations between genotypes of polymorphisms in exon 8 of the PPARGC1A gene and milk production traits in dairy cattle. The study was conducted in a herd of 959 Polish Holstein-Friesian of the black and white cows kept in western Poland. In this study, three polymorphisms within exon 8 of the PPARGC1A gene were analyzed: rs445204772, rs109164431 and rs133669403 and they are responsible for two missense and one synonymous type mutations. All cows were genotyped using the PCR-RFLP method. The PPARGC1A polymorphisms that were studied had the following major allele frequencies: rs445204772 – allele A 0.523; rs109164431 – allele C 0.607 and rs133669403 – allele A 0.546. Statistical analysis was aimed at estimating the effect of individual genotypes on milk performance traits such as milk, protein, and fat yield as well as protein and fat content in milk. For rs445204772 polymorphism, a statistically significant effect on milk yield (P ≤ 0.05) and fat content (P ≤ 0.05, P ≤ 0.01) was observed. Polymorphism rs109164431 significantly (P ≤ 0.05, P ≤ 0.01) affected milk, fat, and protein yield as well as milk fat content. In the case of polymorphism rs133669403, it was found that it affects to a different degree (P ≤ 0.05, P ≤ 0.01) most of the analyzed milk performance traits. The obtained results may contribute to the state of knowledge regarding the identification of the most important SNPs that could be used for the selection of marker assisted dairy cattle.