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Expression of candidate genes for residual feed intake in Angus cattle
Authors:W. Al‐Husseini  C. Gondro  K. Quinn  R. M. Herd  J. P. Gibson  Y. Chen
Affiliation:1. Australian Cooperative Research Centre for Beef Genetic Technologies, University of New England, , Armidale, NSW, Australia;2. The Centre for Genetic Analysis and Applications, University of New England, , Armidale, NSW, 2351 Australia;3. Department of Primary Industries NSW, Beef Industry Centre, Armidale, , NSW, 2351 Australia;4. Department of Primary Industries NSW, Elizabeth Macarthur Agricultural Institute, , Narellan, NSW, 2567 Australia
Abstract:Residual feed intake (RFI) has been adopted in Australia for the purpose of genetic improvement in feed efficiency in beef cattle. RFI is the difference between the observed feed intake of an animal and the predicted feed intake based on its size and growth rate over a test period. Gene expression of eight candidate genes (AHSG, GHR, GSTM1, INHBA, PCDH19, S100A10, SERPINI2 and SOD3), previously identified as differentially expressed between divergent lines of high‐ and low‐RFI animals, was measured in an unselected population of 60 steers from the Angus Society Elite Progeny Test Program using quantitative real‐time PCR. Results showed that the levels of gene expression were significantly correlated with RFI. The genes explain around 33.2% of the phenotypic variance in RFI, and prediction equations using the expression data are reasonably accurate estimators of RFI. The association of these genes with economically important traits, such as other feed efficiency‐related traits and fat, growth and carcass traits, was investigated as well. The expression of these candidate genes was significantly correlated with feed conversion ratio and daily feed intake, which are highly associated with RFI, suggesting a functional role for these genes in modulating feed utilisation. The expression of these genes did not show any association with average daily gain, eye muscle area and carcass composition.
Keywords:beef cattle  gene expression  phenotypic prediction  real‐time PCR  RFI
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