Genetics and Molecular Biology | |
Genomic growth curves of an outbred pig population | |
Fabyano Fonseca E Silva2  Marcos Deon V. De Resende1  Gilson Silvério Rocha2  Darlene Ana S. Duarte2  Paulo Sávio Lopes1  Otávio J.b. Brustolini1  Sander Thus1  José Marcelo S. Viana1  Simone E.f. Guimarães1  | |
[1] ,Universidade Federal de Viçosa Departamento de Estatística Viçosa MG ,Brazil | |
关键词: Bayesian LASSO; nonlinear regression; SNP effects; | |
DOI : 10.1590/S1415-47572013005000042 | |
来源: SciELO | |
【 摘 要 】
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.
【 授权许可】
CC BY
All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License
【 预 览 】
Files | Size | Format | View |
---|---|---|---|
RO202005130148566ZK.pdf | 647KB | download |