Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-22T22:03:36.190Z Has data issue: false hasContentIssue false
  • English
  • Français

Performance, carcass traits and serum metabolomic profile of Nellore males with different genetic potential for post-weaning growth

Published online by Cambridge University Press:  25 October 2019

M. B. da Costa ,
N. R. B. Cônsolo ,
J. Silva ,
V. L. M. Buarque ,
A. R. H. Padilla ,
I. D. Coutinho ,
L. C. G. S. Barbosa ,
L. A. Colnago ,
S. L. Silva  and
A. Saran Netto
M. B. da Costa
Affiliation:
Departamento de Zootecnia, Universidade de São Paulo, 13635-900, Pirassununga, SP, Brazil
N. R. B. Cônsolo
Affiliation:
Departamento de Zootecnia, Universidade de São Paulo, 13635-900, Pirassununga, SP, Brazil
J. Silva
Affiliation:
Departamento de Zootecnia, Universidade de São Paulo, 13635-900, Pirassununga, SP, Brazil
V. L. M. Buarque
Affiliation:
Departamento de Zootecnia, Universidade de São Paulo, 13635-900, Pirassununga, SP, Brazil
A. R. H. Padilla
Affiliation:
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA – Instrumentação), 13560-970, São Carlos, SP, Brazil
I. D. Coutinho
Affiliation:
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA – Instrumentação), 13560-970, São Carlos, SP, Brazil
L. C. G. S. Barbosa
Affiliation:
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA – Instrumentação), 13560-970, São Carlos, SP, Brazil
L. A. Colnago
Affiliation:
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA – Instrumentação), 13560-970, São Carlos, SP, Brazil
S. L. Silva
Affiliation:
Departamento de Zootecnia, Universidade de São Paulo, 13635-900, Pirassununga, SP, Brazil
A. Saran Netto*
Affiliation:
Departamento de Zootecnia, Universidade de São Paulo, 13635-900, Pirassununga, SP, Brazil
*
†E-mail: [email protected]
Get access

Abstract

The BW has been largely used as a selection criterion in genetic selection programmes; however, increases in BW can affect animal metabolism and metabolites. The knowledge of how genetic potential for growth affects the metabolites can give a footprint of growth metabolism. This research aimed to evaluate the effect of genetic potential for post-weaning growth (GG) on performance, carcass traits and serum metabolome of non-castrated Nellore males during the finishing phase. Forty-eight Nellore non-castrated males, with divergent potential for post-weaning growth, were selected and divided into two groups: high potential for post-weaning growth (HG; n = 24) and low potential for post-weaning growth (LG; n = 24). Animals were kept and fed for 90 days where performance and ultrasound carcass traits were evaluated. Blood samples were collected at the beginning and end of feeding period to analyse serum metabolites concentration. The hot carcass weight and dressing percentage were recorded at slaughter. The feedlot performance and carcass traits were not affected by genetic potential. The HG animals had a lower glucose (P = 0.039), glutamate (P = 0.038), glutamine (P = 0.004), greater betaine (P = 0.039) and pyruvate (P = 0.039) compared to the LG group at the beginning of feedlot. In addition, higher creatine phosphate concentrations were observed at the beginning of feeding period, compared to final, for both groups (P = 0.039). In conclusion, the genetic potential for post-weaning growth does not affect performance and carcass traits during the finishing period. Differences in metabolite concentrations can be better found at the beginning of feedlot, providing a footprint of growth metabolism, but similar metabolite concentration at the end of finishing period.

Keywords

animal growthBos indicusgenetic selectionmetabolitesnuclear magnetic resonance
Type
Research Article
Information
animal , Volume 14 , Issue 4 , April 2020 , pp. 873 - 880
Copyright
© The Animal Consortium 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Beckonert, O, Keun, HC, Ebbels, TMD, Bundy, J, Holmes, E and Lindon, JC 2007. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature Protocols 2, 2692–2703.CrossRefGoogle ScholarPubMed
Bell, AW, Greenwood, PL and Ehrhardt, RA 2005. Chapter 1 Regulation of metabolism and growth during prenatal life. Biology of Growing Animals 3, 3–34.CrossRefGoogle Scholar
Campion, B, Keane, MG, Kenny, DA and Berry, DP 2009. Evaluation of estimated genetic merit for carcass weight in beef cattle: live weights, feed intake, body measurements, skeletal and muscular scores, and carcass characteristics. Livestock Science 126, 87–99.CrossRefGoogle Scholar
Churchward-Venne, TA, Burd, NA, Mitchell, CJ, West, DWD, Philp, A, Marcotte, GR, Baker, SK, Baar, K and Phillips, SM 2012. Supplementation of a suboptimal protein dose with leucine or essential amino acids: effects on myofibrillar protein synthesis at rest and following resistance exercise in men. Journal physiology 590, 2751–2765.CrossRefGoogle ScholarPubMed
Cornet, M and Bousset, J 1999. Free amino acids and dipeptides in porcine muscles: differences between red and white muscle. Meat Science 51, 215–219.CrossRefGoogle Scholar
Delgado, CL 2003. Rising consumption of meat and milk in developing countries has created a new food revolution. The Journal of Nutrition 133, 3907S–3910S.CrossRefGoogle ScholarPubMed
Fiol, C, Carriquiry, M and Ungerfeld, R 2017. Social dominance in prepubertal dairy heifers allocated in continuous competitive dyads: effects on body growth, metabolic status, and reproductive development. Journal of Dairy Science 100, 2351–2359.CrossRefGoogle ScholarPubMed
Galindo, F, Newberry, RC and Mendl, M 2011. Social conditions. In Animal welfare (ed. Appleby, MC, Mench, J, Olsson, A and Hughes, BO), pp. 228–245. CABI Publishing, Wallingford, UK.CrossRefGoogle Scholar
Goldansaz, SA, Guo, AC, Sajed, T, Steele, MA, Plastow, GS and Wishart, DS 2017. Livestock metabolomics and the livestock metabolome: a systematic review. PLoS ONE 12, 1–26.CrossRefGoogle ScholarPubMed
Kaneko, J, Harvey, J and Brus, M 2008. Clinical biochemistry of domestic animal, 6th edition. Elsevier Inc., San Diego, CA, USA.Google Scholar
Karisa, BK, Thomson, J, Wang, Z, Li, C, Montanholi, YR, Miller, SP, Moore, SS and Plastow, GS 2014. Plasma metabolites associated with residual feed intake and other productivity performance traits in beef cattle. Livestock Science 165, 200–211.CrossRefGoogle Scholar
Keady, SM, Kenny, DA, Ohlendieck, K, Doyle, S, Keane, MG and Waters, SM 2013. Proteomic profiling of bovine M. longissimus lumborum from Crossbred Aberdeen Angus and Belgian Blue sired steers varying in genetic merit for carcass weight. Journal of Animal Science 91, 654–665.CrossRefGoogle ScholarPubMed
Li, J, Greenwood, PL, Cockett, NE, Hadfield, TS, Vuocolo, T, Byrne, K, White, JD, Tellam, RL and Schirra, HJ 2014. Impacts of the callipyge mutation on ovine plasma metabolites and muscle fibre type. PLoS ONE 9, 1–5.Google ScholarPubMed
Lopes, FB, Da Silva, MC, Magnabosco, CU, Narciso, MG and Sainz, RD 2016. Selection indices and multivariate analysis show similar results in the evaluation of growth and carcass traits in beef cattle. PLoS ONE 11, 1–21.Google Scholar
Madella-Oliveira, A de F, Quirino, CR, Ruiz-Miranda, CR and Fonseca, FA 2012. Social behaviour of buffalo heifers during the establishment of a dominance hierarchy. Livestock Science 146, 73–79.CrossRefGoogle Scholar
Martínez-Miró, S, Tecles, F, Ramón, M, Escribano, D, Hernández, F, Madrid, J, Orengo, J, Martínez-Subiela, S, Manteca, X and Cerón, JJ 2016. Causes, consequences and biomarkers of stress in swine: an update. BMC Veterinary Research 12, 1–9.CrossRefGoogle ScholarPubMed
Miranda-de la Lama, GC, Pascual-Alonso, M, Guerrero, A, Alberti, P, Alierta, S, Sans, P, Gajan, JP, Villarroel, M, Dalmau, A, Velarde, A, Campo, MM, Galindo, F, Santolaria, MP, Sañudo, C and María, GA 2013. Influence of social dominance on production, welfare and the quality of meat from beef bulls. Meat Science 94, 432–437.CrossRefGoogle ScholarPubMed
Nelson, DL, Lehninger, AL and Cox, MM 2008. Lehninger principles of biochemistry, 5th edition. W.H. Freeman, New York, NY, USA.Google Scholar
Pearson, H 2007. Meet the human metabolome. Nature 446, 8.CrossRefGoogle ScholarPubMed
Straadt, IK, Aaslyng, MD and Bertram, HC 2014. An NMR-based metabolomics study of pork from different crossbreeds and relation to sensory perception. Meat Science 96, 719–728.CrossRefGoogle ScholarPubMed
Tiziani, S, Emwas, AH, Lodi, A, Ludwig, C, Bunce, CM, Viant, MR and Günther, UL 2008. Optimized metabolite extraction from blood serum for 1H nuclear magnetic resonance spectroscopy. Analytical Biochemistry 377, 16–23.CrossRefGoogle ScholarPubMed
Tomkins, NW, Harper, GS, Bruce, HL and Hunter, RA 2006. Effect of different post-weaning growth paths on long-term weight gain, carcass characteristics and eating quality of beef cattle. Australian Journal of Experimental Agriculture 46, 1571–1578.CrossRefGoogle Scholar
Weiss, WP, Conrad, HR, St-Pierre, NR 1992. A theoretically-based model for predicting total digestible values of forages and concentrates. Animal Feed Science and Technology 39, 95–110.CrossRefGoogle Scholar
Zhan, XA, Li, JX, Xu, ZR and Zhao, RQ 2006. Effects of methionine and betaine supplementation on growth performance, carcass composition and metabolism of lipids in male broilers. British Poultry Science 47, 576–580.CrossRefGoogle Scholar
Zuin, RG, Buzanskas, ME, Caetano, SL, Venturini, GC, Guidolin, DGF, Grossi, DA, Chud, TCS, Paz, CCP, Lôbo, RB and Munari, DP 2012. Genetic analysis on growth and carcass traits in Nellore cattle. Meat Science 91, 352–357.CrossRefGoogle Scholar