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- 저자 : ( Carlos Alberto Mezzadra ) (검색결과 1 건)
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( Daniel Estanislao Goszczynski ),( Juliana Papaleo Mazzucco ),( Maria Veronica Ripoli ),( Edgardo Leopoldo Villarreal ),( Andres Rogberg-munoz ),( Carlos Alberto Mezzadra ),( Lilia Magdalena Melucci 한국동물자원과학회(구 한국축산학회) 2016 한국축산학회지 Vol.58 No.4
Background: Peroxisome proliferator-activated receptor gamma (PPARG), CCAAT/enhancer binding protein alpha (CEBPA) and retinoid X receptor alpha (RXRA) are nuclear transcription factors that play important roles in regulation of adipogenesis and fat deposition. The objectives of this study were to characterise the variability of these three candidate genes in a mixed sample panel composed of several cattle breeds with different meat quality, validate single nucleotide polymorphisms (SNPs) in a local crossbred population (Angus - Hereford - Limousin) and evaluate their effects on meat quality traits (backfat thickness, intramuscular fat content and fatty acid composition), supporting the association tests with bioinformatic predictive studies. Results: Globally, nine SNPs were detected in the PPARG and CEBPA genes within our mixed panel, including a novel SNP in the latter. Three of these nine, along with seven other SNPs selected from the Single Nucleotide Polymorphism database (SNPdb), including SNPs in the RXRA gene, were validated in the crossbred population (N = 260). After validation, five of these SNPs were evaluated for genotype effects on fatty acid content and composition. Significant effects were observed on backfat thickness and different fatty acid contents (P < 0.05). Some of these SNPs caused slight differences in mRNA structure stability and/or putative binding sites for proteins. Conclusions: PPARG and CEBPA showed low to moderate variability in our sample panel. Variations in these genes, along with RXRA, may explain part of the genetic variation in fat content and composition. Our results may contribute to knowledge about genetic variation in meat quality traits in cattle and should be evaluated in larger independent populations.
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