Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-25T04:21:36.043Z Has data issue: false hasContentIssue false

Phenotypic plasticity of composite beef cattle performance using reaction norms model with unknown covariate

Published online by Cambridge University Press:  27 September 2012

M. L. Santana Jr*
Affiliation:
Grupo de Melhoramento Animal de Mato Grosso, Instituto de Ciências Agrárias e Tecnológicas, Universidade Federal de Mato Grosso, Campus Universitário de Rondonópolis, MT-270, Km 06, CEP 78735-901, Rondonópolis, MT, Brazil Grupo de Melhoramento Animal e Biotecnologia, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, C. Postal 23, CEP 13635-970, Pirassununga, SP, Brazil
J. P. Eler
Affiliation:
Grupo de Melhoramento Animal e Biotecnologia, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, C. Postal 23, CEP 13635-970, Pirassununga, SP, Brazil
F. F. Cardoso
Affiliation:
Embrapa Pecuária Sul, BR 153 – Km 603, C. Postal 242, CEP 96401-970, Bagé, RS, Brazil
L. G. Albuquerque
Affiliation:
Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, CEP 14884-900, Jaboticabal, SP, Brazil
J. B. S. Ferraz
Affiliation:
Grupo de Melhoramento Animal e Biotecnologia, Faculdade de Zootecnia e Engenharia de Alimentos, Universidade de São Paulo, C. Postal 23, CEP 13635-970, Pirassununga, SP, Brazil
*
Get access

Abstract

The objective of the present study was to determine the presence of genotype by environment interaction (G × E) and to characterize the phenotypic plasticity of birth weight (BW), weaning weight (WW), postweaning weight gain (PWG) and yearling scrotal circumference (SC) in composite beef cattle using the reaction norms model with unknown covariate. The animals were born between 1995 and 2008 on 33 farms located throughout all Brazilian biomes between latitude −7° and −31°, longitude −40° and −63°. The contemporary group was chosen as the environmental descriptor, that is, the environmental covariate of the reaction norms. In general, higher estimates of direct heritability were observed in extreme favorable environments. The mean of direct heritability across the environmental gradient ranged from 0.05 to 0.51, 0.09 to 0.43, 0.01 to 0.43 and from 0.12 to 0.26 for BW, WW, PWG and SC, respectively. The variation in direct heritability observed indicates a different response to selection according to the environment in which the animals of the population are evaluated. The correlation between the level and slope of the reaction norm for BW and PWG was high, indicating that animals with higher average breeding values responded better to improvement in environmental conditions, a fact characterizing a scale of G × E. Low correlation between the intercept and slope was obtained for WW and SC, implying re-ranking of animals in different environments. Genetic variation exists in the sensitivity of animals to the environment, a fact that permits the selection of more plastic or robust genotypes in the population studied. Thus, the G × E is an important factor that should be considered in the genetic evaluation of the present population of composite beef cattle.

Type
Breeding and genetics
Copyright
Copyright © The Animal Consortium 2012

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

Albuquerque, LG, Meyer, K 2001. Estimates of covariance functions for growth from birth to 630 days of age in Nelore Cattle. Journal of Animal Science 79, 27762789.Google Scholar
Alencar, MM, Mascioli, AS, Freitas, AR 2005. Evidences of genotype × environment interaction for growth traits in beef cattle. Brazilian Journal of Animal Science 34, 489495.Google Scholar
Bennett, GL, Gregory, KE 1996. Genetic (co)variances among birth weight, 200-day weight, and postweaning gain in composites and parental breeds of beef cattle. Journal of Animal Science 74, 25982611.Google Scholar
Bocchi, AL, Oliveira, HN, Ferraz, JBS, Eler, JP 2008. Multibreed genetic evaluation for pre-weaning daily gain in a composite cattle population. Brazilian Journal of Animal Science 37, 12071215.Google Scholar
Bradshaw, AD 1965. Evolutionary significance of phenotypic plasticity in plants. Advances in Genetics 13, 115155.Google Scholar
Burrow, HM 2001. Variances and covariances between productive and adaptive traits and temperament in a composite breed of tropical beef cattle. Livestock Production Science 70, 213233.CrossRefGoogle Scholar
Calus, MPL, Groen, AF, de Jong, G 2002. Genotype × environment interaction for protein yield in Dutch dairy cattle as quantified by different models. Journal of Dairy Science 85, 31153123.Google Scholar
Cardoso, FF 2010. Application of Bayesian inference in animal breeding using the Intergen program, Manual of Version 1.2., Embrapa Pecuária Sul, Bagé, RS, 30 pp. Retrieved November 29, 2011, from http://www.cppsul.embrapa.br/unidade/servicos/intergenGoogle Scholar
Cardoso, LL, Braccini Neto, J, Cardoso, FF, Cobuci, JA, Biassus, IO, Barcellos, JOJ 2011. Hierarchical Bayesian models for genotype × environment estimates in post-weaning gain of Hereford bovine via reaction norms. Brazilian Journal of Animal Science 40, 294300.Google Scholar
Corrêa, MBB, Dionello, NJL, Cardoso, FF 2009. Genotype by environment interaction characterization and model comparison for post weaning gain adjustment of Devon cattle via reaction norms. Brazilian Journal of Animal Science 38, 14681477.Google Scholar
de Jong, G, Bijma, P 2002. Selection and phenotypic plasticity in evolutionary biology and animal breeding. Livestock Production Science 78, 195214.Google Scholar
DeNise, SK, Torabi, M, Ray, DE, Rice, R 1988. Genetic parameter estimates for preweaning traits of beef cattle in a stressful environment. Journal of Animal Science 66, 18991906.Google Scholar
Dias, LT, Albuquerque, LG, Tonhati, H, Teixeira, RA 2005. Estimation of genetic parameters for weight in different ages in Tabapuã cattle. Brazilian Journal of Animal Science 34, 19141919.Google Scholar
Eler, JP, Ferraz, JBS, Golden, BL, Pereira, E 2000. Influence of sire × herd interaction on the estimation of correlation between direct and maternal genetic effects in Nellore cattle. Brazilian Journal of Animal Science 29, 16421648.Google Scholar
Eler, JP, Silva, JAIIV, Evans, JL, Ferraz, JBS, Dias, F, Golden, BL 2004. Additive genetic relationships between heifer pregnancy and scrotal circumference in Nellore cattle. Journal of Animal Science 82, 25192527.Google Scholar
Eriksson, S, Näsholm, A, Johansson, K, Philipsson, J 2004. Genetic parameters for calving difficulty, stillbirth, and birth weight for Hereford and Charolais at first and later parities. Journal of Animal Science 82, 375383.Google Scholar
Falconer, DS 1990. Selection in different environments: effects on environmental sensitivity (reaction norm) and on mean performance. Genetical Research 56, 5770.Google Scholar
Falconer, DS, Mackay, TFC 1996. Introduction to Quantitative Genetics, 4th edition. Longman Group Ltd, Essex, UK.Google Scholar
Ferraz, JBS, Eler, JP, Golden, BL 1999. A formação do composto Montana Tropical. Revista Brasileira de Reprodução Animal 23, 115117.Google Scholar
Fikse, WF, Rekaya, R, Weigel, KA 2003. Assessment of environmental descriptors for studying genotype by environment interaction. Livestock Production Science 82, 223231.Google Scholar
Gregory, KE, Cundiff, LV, Koch, RM 1995. Genetic and phenotypic (co)variances for growth and carcass traits of purebred and composite populations of beef cattle. Journal of Animal Science 73, 19201926.CrossRefGoogle ScholarPubMed
Kirkpatrick, M, Heckman, N 1989. A quantitative genetic model for growth, shape, reaction norms, and other infinite-dimensional characters. Journal of Mathematical Biology 27, 429450.Google Scholar
Kolmodin, R, Strandberg, E, Danella, B, Jorjani, H 2004. Reaction norms for protein yield and days open in Swedish red and white dairy cattle in relation to various environmental variables. Acta Agriculturae Scandinavica 54, 139151.CrossRefGoogle Scholar
Kolmodin, R, Strandberg, E, Madsen, P, Jensen, J, Jorjani, H 2002. Genotype by environment interaction in Nordic dairy studied by use of reaction norms. Acta Agriculturae Scandinavica 52, 1124.Google Scholar
Marcondes, CR, Bergmann, JAG, Eler, JP, Ferraz, JBS, Pereira, JCC, Penna, VM 2000. Analysis of some selection criteria for growth traits in Nellore cattle. Arquivo Brasileiro de Medicina Veterinária e Zootecnia 52, 8389.Google Scholar
Mattar, M, Silva, LOC, Alencar, MM, Cardoso, FF 2011. Genotype × environment interaction for long-yearling weight in Canchim cattle quantified by reaction norm analysis. Journal of Animal Science 89, 23492355.Google Scholar
Namkoong, G 1985. The influence of composite traits on genotype by environment relations. Theoretical and Applied Genetics 70, 315317.CrossRefGoogle ScholarPubMed
Pégolo, NT, Oliveira, HN, Albuquerque, LG, Bezerra, LAF, Lôbo, RB 2009. Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models. Genetics and Molecular Biology 32, 281287.Google Scholar
Pollott, GE, Greeff, JC 2004. Genotype × environment interactions and genetic parameters for fecal egg count and production traits of Merino sheep. Journal of Animal Science 82, 28402851.Google Scholar
Santana, ML Jr, Eler, JP, Cardoso, FF, Albuquerque, LG, Bignardi, AB, Ferraz, JBS 2012a. Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil. Livestock Science (in press).Google Scholar
Santana, ML Jr, Eler, JP, Ferraz, JBS, Mattos, EC 2012b. Genetic relationship between growth and reproductive traits in Nellore cattle. Animal 6, 565570.Google Scholar
Stearns, SC 1989. The evolutionary significance of phenotypic plasticity. BioScience 39, 436445.Google Scholar
Strandberg, E, Brotherstone, S, Wall, E, Coffey, MP 2009. Genotype by environment interaction for first-lactation female fertility traits in UK dairy cattle. Journal of Dairy Science 92, 34373446.Google Scholar
Strandberg, E, Kolmodin, R, Madsen, P, Jensen, J, Jorjani, H 2000. Genotype by environment interaction in Nordic dairy cattle studied by use of reaction norms. Interbull Bulletin 25, 4145.Google Scholar
Su, G, Madsen, P, Lund, MS, Sorensen, D, Korsgaard, IR, Jensen, J 2006. Bayesian analysis of the linear reaction norm model with unknown covariates. Journal of Animal Science 84, 16511657.Google Scholar
Toral, FLB, Silva, LOC, Martins, EN, Gondo, A, Simonelli, SM 2004. Genotype × environment interaction in growth traits of Nellore cattle of Mato Grosso do Sul. Brazilian Journal of Animal Science 33, 14451455.Google Scholar
Vargas, CA, Elzo, MA, Chase, CC Jr, Chenoweth, PJ, Olson, TA 1998. Estimation of genetic parameters for scrotal circumference, age at puberty in heifers, and hip height in Brahman cattle. Journal of Animal Science 76, 25362541.CrossRefGoogle ScholarPubMed
Via, S, Lande, R 1985. Genotype–environment interaction and the evolution of phenotypic plasticity. Evolution 39, 505522.CrossRefGoogle ScholarPubMed
Supplementary material: Image

Santana Supplementary Material

Figure

Download Santana Supplementary Material(Image)
Image 3.9 MB