Browse > Article
http://dx.doi.org/10.1186/s40781-016-0095-3

Genetic characterisation of PPARG, CEBPA and RXRA, and their influence on meat quality traits in cattle  

Goszczynski, Daniel Estanislao (Instituto de Genetica Veterinaria "Ing. Fernando Noel Dulout" (IGEVET), CONICET, Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata)
Mazzucco, Juliana Papaleo (Unidad Integrada INTA Balcarce-Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata)
Ripoli, Maria Veronica (Instituto de Genetica Veterinaria "Ing. Fernando Noel Dulout" (IGEVET), CONICET, Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata)
Villarreal, Edgardo Leopoldo (Unidad Integrada INTA Balcarce-Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata)
Rogberg-Munoz, Andres (Instituto de Genetica Veterinaria "Ing. Fernando Noel Dulout" (IGEVET), CONICET, Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata)
Mezzadra, Carlos Alberto (Unidad Integrada INTA Balcarce-Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata)
Melucci, Lilia Magdalena (Unidad Integrada INTA Balcarce-Facultad de Ciencias Agrarias, Universidad Nacional de Mar del Plata)
Giovambattista, Guillermo (Instituto de Genetica Veterinaria "Ing. Fernando Noel Dulout" (IGEVET), CONICET, Facultad de Ciencias Veterinarias, Universidad Nacional de La Plata)
Publication Information
Journal of Animal Science and Technology / v.58, no.4, 2016 , pp. 14.1-14.9 More about this Journal
Abstract
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.
Keywords
Polymorphism; Variation; Association; Cows; Beef; SNPs;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Schneider S, Roessli D, Excoffier L. Arlequin, a software for Population Genetics Data Analysis. University of Geneva: Ver 2.0. Genetics and Biometry Lab, Department of Anthropology; 2000.
2 SAS software. Copyright, SAS Institute Inc., Cary, NC, USA.
3 Falconer DS, Mackay TFC. Introduction to Quantitative Genetics. Harlow: Addison Wesley Longman Limited; 1996.
4 Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc B. 1995;57:289-300.
5 The Codon Usage Database. http://www.kazusa.or.jp/codon/. Bos taurus [gbmam]: 13374. Accessed 6 January 2016.
6 Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 2003;31(13):3406-15.   DOI
7 Cook KB, Kazan H, Zuberi K, Morris Q, Hughes TR. RBPDB: a database of RNA-binding specificities. Nucleic Acids Res. 2011;39:D301-8.   DOI
8 Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263-5.   DOI
9 Sevane N, Armstrong E, Cortés O, Wiener P, Pong Wong R, Dunner S, Gemqual Consortium. Association of bovine meat quality traits with genes included in the PPARG and PPARGC1A networks. Meat Sci. 2013;94:328-35.   DOI
10 USDA (United States Department of Agriculture). Livestock and Poultry: World Markets and Trade. Foreign Agricultural Service. 2015. http://apps.fas. usda.gov/psdonline/circulars/livestock_poultry.pdf. Accessed 18 March 2016.
11 Giovambattista G, Ripoli MV, Lirón JP, Villegas Castagnasso EE, Peral-García P, Lojo MM. DNA typing in a cattle stealing case. J Forensic Sci. 2001;46(6): 1484-6.
12 Goszczynski DE, Mazzucco JP, Ripoli MV, Villarreal EL, Rogberg-Muñoz A, Mezzadra CA, Melucci LM, Giovambattista G. Characterisation of the bovine gene LIPE and possible influence on fatty acid composition of meat. Meta Gene. 2014;16(2):746-60.
13 Shahidi F. Lipid-derived flavors in meat products. In: Kerry J, Kerry J, Ledward D, editors. Meat processing: improving meat quality. Cambridge: Woodhead Publishing Limited; 2002. p. 105-21.
14 Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA, McWilliam H, Valentin F, Wallace IM, Wilm A, Lopez R, Thompson JD, Gibson TJ, Higgins DG. Clustal W and Clustal X version 2.0. Bioinformatics. 2007;23:2947-8.   DOI
15 The Single Nucleotide Polymorphism Database (dbSNP). http://www.ncbi. nlm.nih.gov/snp. Accessed 6 January 2016.
16 Sequenom, Inc. https://www.sequenom.com. Accessed 6 January 2016.
17 Du M, Yin J, Zhu MJ. Cellular signaling pathways regulating the initial stage of adipogenesis and marbling of skeletal muscle. Meat Sci. 2010;86(1):103-9.   DOI
18 Hausman GJ, Dodson MV, Ajuwon K, Azain M, Barnes KM, Guan LL, Jiang Z, Poulos SP, Sainz RD, Smith S, Spurlock M, Novakofski J, Fernyhough ME, Bergen WG. Board-invited review: the biology and regulation of preadipocytes and adipocytes in meat animals. J Anim Sci. 2009;87(4):1218-46.   DOI
19 Broos S, Soete A, Hooghe B, Moran R, van Roy F, De Bleser P. PhysBinder: Improving the prediction of transcription factor binding sites by flexible inclusion of biophysical properties. Nucleic Acids Res. 2013;41:W531-4.   DOI
20 Bovine HapMap Consortium. Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds. Science. 2009;324(5926):528-32.   DOI
21 Oh D, Lee Y, Lee C, Chung E, Yeo J. Association of bovine fatty acid composition with missense nucleotide polymorphism in exon 7 of peroxisome proliferator-activated receptor gamma gene. Anim Genet. 2011; 43(4):474.
22 Barendse W. Haplotype Analysis Improved Evidence for Candidate Genes for Intramuscular Fat Percentage from a Genome Wide Association Study of Cattle. PLoS One. 2011;6(12):e29601. doi:10.1371/journal.pone.0029601.   DOI
23 Fan YY, Zan LS, Fu CZ, Tian WQ, Wang HB, Liu YY, Xin YP. Three novel SNPs in the coding region of PPAR${\gamma}$ gene and their associations with meat quality traits in cattle. Mol Biol Rep. 2011;38(1):131-7.   DOI
24 He H, Liu X, Gu Y, Liu Y, Yang J. Effect of genetic variation of CEBPA gene on body measurement and carcass traits of Qinchuan cattle. Mol Biol Rep. 2011;38:4965-9.   DOI
25 Wang H, Zan LS, Wang HB, Song FB. A novel SNP of the C/EBP${\alpha}$ gene associated with superior meat quality in indigenous Chinese cattle. Gen Mol Res. 2011;10(3):2069-77.
26 Rousset F. GENEPOP'007: a complete re-implementation of the GENEPOP software for Windows and Linux. Mol Ecol Res. 2008;8:103-6.   DOI