Abdelmajid El Hou
ABSTRACT
Meat quality is a complex and multifactorial trait. Several factors can influence this character, including genetic and environmental factors. Based on phenotypic data for three traits related to muscular characteristics and /or meat quality in Charolais French beef cattle breed, 108 QTLs (Quantitative Trait Loci) related to these phenotypes were identified using a Bayesian approach. However, this method does not give a confidence interval. The objective of this study is to determine the confidence intervals of these QTLs based on linkage disequilibrium analysis in the Charolais breed and to identify candidate genes for the tenderness score based on mouse phenotype. QTL intervals were defined with a range from 1.93 to 20.80 Mb and an average of 13.04 Mb. Thus, 27 putative candidate genes for the tenderness score have been identified.
- FranceAgriMer, 2018. "Fiches produits FranceAgriMer - viande bovine", publications, July 2018.Google Scholar
- Dubuisson, C., Lioret, S., Touvier, M., Dufour, A., Calamassi-Tran, G., Volatier, J., & Lafay, L. (2010). Trends in food and nutritional intakes of French adults from 1999 to 2007: Results from the INCA surveys. British Journal of Nutrition, 103(7), 1035--1048.Google ScholarCross Ref
- Geay, Y., D. Bauchart, J. F. Hocquette, and J. Culioli. 2001. Effect of nutritional factors on biochemical, structural and metabolic characteristics of muscles in ruminants, consequences on dietetic value and sensorial qualities of meat. Reprod. Nutr. Dev. 41:1--26.Google ScholarCross Ref
- Allais, S., H. Levéziel, N. Payet-Duprat, J. F. Hocquette, J. Lepetit, S. Rousset, C. Denoyelle, C. Bernard-Capel, L. Journaux, A. Bonnot, and G. Renand. 2010. The two mutations Q204X and nt821 of the myostatin gene affect carcass and meat quality in heterozygous young bulls of French beef breeds. J. Anim. Sci. 88:446--454.Google ScholarCross Ref
- Warner RD, Greenwood PL, Pethick DW, Ferguson DM. Genetic and environmental effects on meat quality. Meat Sci. 2010;86:171--83.Google Scholar
- Allais, S., H. Levéziel, N. Payet-Duprat, J. F. Hocquette, J. Lepetit, S. Rousset, C. Denoyelle, C. Bernard-Capel, L. Journaux, A. Bonnot, and G. Renand. 2010. The two mutations Q204X and nt821 of the myostatin gene affect carcass and meat quality in heterozygous young bulls of French beef breeds. J. Anim. Sci. 88:446--454.Google ScholarCross Ref
- Barendse, W. J. 2002. DNA markers for meat tenderness. International patent application PCT/AU02/00122. International patent publication WO 02/064820 A1. 22 August 2002.Google Scholar
- Han, SH., Cho, IC., Ko, MS. et al. A promoter polymorphism of MSTN g.--371T>A and its associations with carcass traits in Korean cattl. Mol Biol Rep (2012) 39: 3767.Google Scholar
- F. S. Schenkel, S. P. Miller, Z. Jiang, I. B. Mandell, X. Ye, H. Li, J. W. Wilton; Association of a single nucleotide polymorphism in the calpastatin gene with carcass and meat quality traits of beef cattle, Journal of Animal Science, Volume 84, Issue 2, 1 February 2006, Pages 291--299.Google Scholar
- E. Casas, S. N. White, T. L. Wheeler, S. D. Shackelford, M. Koohmaraie, D. G. Riley, C. C. Chase, D. D. Johnson, T. P. L. Smith; Effects of calpastatin and μ-calpain markers in beef cattle on tenderness traits, Journal of Animal Science, Volume 84, Issue 3, 1 April 2006, Pages 520--525.Google Scholar
- Boichard D, Grohs C, Bourgeois F, Cerqueira F, Faugeras R, Neau A, Rupp R, Amigues Y, Boscher MY, Levéziel H. Detection of genes influencing economic traits in three French dairy cattle breeds. Genet Sel Evol. 2003;35:77--101.Google Scholar
- Legarra, A., Croiseau, P., Sanchez, M. P., Teyssèdre S., Sallé, G., Allais, S., Fritz, S., Rénée Moreno, C., Ricard, A., and Elsen, J; M., Genetics Selection Evolution (2015) 47:6.Google Scholar
- Habier D, Fernando RL, Kizilkaya K, Garrick DJ: Extension of the bayesian alphabet for genomic selection. BMC Bioinformatics 2011, 12(1):186.Google Scholar
- A van den Berg, I., Fritz, S., & Boichard, D. (2013). QTL fine mapping with Bayes C(π): a simulation study. Genetics, selection, evolution: GSE, 45(1), 19.Google Scholar
- M. Gunia, R. Saintilan, E. Venot, C. Hozé, M. N. Fouilloux, F. Phocas; Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers, Journal of Animal Science, Volume 92, Issue 8, 1 August 2014, Pages 3258--3269.Google Scholar
- Sargolzaei M, Chesnais JP, Schenkel F. A new approach for efficient genotype imputation using information from relatives. BMC Genom. 2014;15:478.Google Scholar
- Clayton D (2015). snpStats: SnpMatrix and XSnpMatrix classes and methods. R package version 1.28.0.Google Scholar
- Shaun Purcell and Christopher Chang, PLINK v1.90b3.34, www.cog-genomics.org/plink/1.9/.Google Scholar
- Durinck S, Spellman P, Birney E, Huber W (2009). "Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt." Nature Protocols, 4, 1184--1191.Google ScholarCross Ref
- Pritchard JK, Przeworski M (2001). Linkage disequilibrium in humans: models and data. Am J Hum Genet 69: 1--14.Google ScholarCross Ref
- Ron, M., & Weller, J. I. (2007). From QTL to QTN identification in livestock - Winning by points rather than knock-out: A review. Animal Genetics, 38(5), 429--439.Google ScholarCross Ref
- T. Yoshida, Y. Pan, H. Hanada, Y. Iwata and M. Shigekawa: Bidirectional signaling between sarcoglycans and the integrin adhesion system in cultured L6 myocytes. J Biol Chem, 273(3), 1583--90 (1998)Google Scholar
- Hack, A. A., Ly, C. T., Jiang, F., Clendenin, C. J., Sigrist, K. S., Wollmann, R. L., & Mcnally, E. M. (1998). γ-Sarcoglycan Deficiency Leads to Muscle Membrane Defects and Apoptosis Independent of Dystrophin, 142(5), 1279--1287.Google Scholar
- MacArthur, Daniel G, Seto, Jane T, Raftery, Joanna M, Quinlan, Kate G, Huttley, Gavin A, Hook, Jeff W, Lemckert, Frances A, Kee, Anthony J, Edwards, Michael R, Berman, Yemima, Hardeman, Edna C, Gunning, Peter W, Easteal, Simon, Yang, Nan, North, Kathryn N, (2007). Loss of ACTN3 gene function alters mouse muscle metabolism and shows evidence of positive selection in humans. Nature Genetics.Google Scholar
- Stohn, J. P., Perreault, N. G., Wang, Q., Liaw, L., & Lindner, V. (2012). Cthrc1, a Novel Circulating Hormone Regulating Metabolism. PLoS ONE, 7(10).Google Scholar
- Walji, Tezin A et al. "Characterization of metabolic health in mouse models of fibrillin-1 perturbation" Matrix biology: journal of the International Society for Matrix Biology vol. 55 (2016): 63--76.Google Scholar
- Zhixiong Li, Yaou Xu, Yaqiu Lin. Transcriptome analyses reveal genes of alternative splicing associated with muscle development in chickens. Gene. Volume 676, 2018, Pages 146--155,Google Scholar
Index Terms
- Fine QTL mapping for meat quality traits in French Charolaise breed using HD SNP data
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