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Silva FF, de Resende MD, Rocha GS, et al. Genomic growth curves of an outbred pig population. Genet Mol Biol. 2013;36(4):520-7doi: 10.1590/S1415-47572013005000042.
Silva, F. F., de Resende, M. D., Rocha, G. S., Duarte, D. A., Lopes, P. S., Brustolini, O. J., Thus, S., Viana, J. M., & Guimarães, S. E. (2013). Genomic growth curves of an outbred pig population. Genetics and molecular biology, 36(4), 520-7. https://doi.org/10.1590/S1415-47572013005000042
Silva, Fabyano Fonseca E, et al. "Genomic growth curves of an outbred pig population." Genetics and molecular biology vol. 36,4 (2013): 520-7. doi: https://doi.org/10.1590/S1415-47572013005000042
Silva FF, de Resende MD, Rocha GS, Duarte DA, Lopes PS, Brustolini OJ, Thus S, Viana JM, Guimarães SE. Genomic growth curves of an outbred pig population. Genet Mol Biol. 2013 Dec;36(4):520-7. doi: 10.1590/S1415-47572013005000042. Epub 2013 Oct 25. PMID: 24385855; PMCID: PMC3873183.
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Genet Mol Biol. 2013 Dec;36(4):520-7. doi: 10.1590/S1415-47572013005000042. Epub 2013 Oct 25.

Genomic growth curves of an outbred pig population.

Genetics and molecular biology

Fabyano Fonseca E Silva, Marcos Deon V de Resende, Gilson Silvério Rocha, Darlene Ana S Duarte, Paulo Sávio Lopes, Otávio J B Brustolini, Sander Thus, José Marcelo S Viana, Simone E F Guimarães

Affiliations

  1. Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG, Brazil .
  2. Embrapa Florestas/Universidade Federal de Viçosa, Colombo, PR, Brazil .
  3. Departamento de Estatística, Universidade Federal de Viçosa, Viçosa, MG, Brazil . ; Departamento de Ciência Animal, Universidade Federal de Viçosa, Viçosa, MG, Brazil .
  4. Departamento de Ciência Animal, Universidade Federal de Viçosa, Viçosa, MG, Brazil .
  5. Instituto de Biotecnologia Aplicada à Agropecuária, Universidade Federal de Viçosa, Viçosa, MG, Brazil .
  6. Department of Animal Sciences, Wageningen University, Wageningen, Netherlands .
  7. Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa, MG, Brazil .

PMID: 24385855 PMCID: PMC3873183 DOI: 10.1590/S1415-47572013005000042

Abstract

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

Keywords: Bayesian LASSO; SNP effects; nonlinear regression

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