Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle

Karisa, B. K., Thomson, J., Wang, Z., Stothard, P., Moore, S. S. and Plastow, G. S. (2013) Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle. Journal of Animal Science, 91 8: 3502-3513. doi:10.2527/jas.2012-6170


Author Karisa, B. K.
Thomson, J.
Wang, Z.
Stothard, P.
Moore, S. S.
Plastow, G. S.
Title Candidate genes and single nucleotide polymorphisms associated with variation in residual feed intake in beef cattle
Journal name Journal of Animal Science   Check publisher's open access policy
ISSN 0021-8812
1525-3163
Publication date 2013-08
Sub-type Article (original research)
DOI 10.2527/jas.2012-6170
Volume 91
Issue 8
Start page 3502
End page 3513
Total pages 12
Place of publication Savoy, IL, United States
Publisher American Society of Animal Science
Collection year 2014
Language eng
Formatted abstract
The candidate gene approach was used to identify genes associated with residual feed intake (RFI) in beef steers. The approach uses prior knowledge of gene functions to predict their biological role in the variation observed in a trait. It is suited to identify genes associated with complex traits where each gene has a relatively small effect. First, positional candidate genes were identified within the genomic positions of previously reported QTL associated with component traits related to RFI such as dry matter intake (DMI), growth, feed conversion ratio (FCR), average daily gain (ADG), and energy balance. Secondly, the positional candidate genes were prioritized into functional candidate genes according to their biological functions and their relationship with the biological processes associated with RFI including carbohydrate, fat and protein metabolism, thermoregulation, immunity and muscle activity. Single nucleotide polymorphisms (SNPs) located within the functional candidate genes were identified using mRNA sequences and prioritized into functional classes such as non-synonymous (nsSNP), synonymous (sSNP) or intronic SNP. A total of 117 nsSNP were considered as functional SNP and genotyped in steers at the University of Alberta ranch in Kinsella. Multiple marker association analysis in ASReml was performed using RFI data obtained from 531 beef steers. Twenty-five SNP were significantly associated with RFI (P < 0.05) accounting for 19.7% of the phenotypic variation. Using SIFT program to predict the effect of the SNP on the function of the corresponding protein, 3 of the 25 SNP were predicted to cause a significant effect on protein function (P < 0.05). One of the 3 SNP was located in the GHR gene and was also associated with a significant effect on the tertiary structure of the GHR protein (P < 0.05) as modeled using SWISSModel software. Least square means for each genotype were estimated and an over-dominance effect was observed for the SNP located in the GHR, CAST, ACAD11 and UGT3A1 genes. In addition, 2 other SNP showed a dominance effect and 3 genes had an additive effect. Gene network analysis performed in Ingenuity pathway analysis (IPA) software (Ingenuity Systems, www.ingenuity.com) indicated that the significant genes were involved in biological pathways such as lipid, protein and energy metabolism, electron transport and membrane signaling. The genes in this study, if validated in other beef cattle populations, may be useful for marker assisted selection for feed efficiency.
Keyword Beef cattle
Candidate genes
Gene networks
Residual feed intake
Quantitative trait loci
Growth-factor-I
Carcass traits
Meat quality
Divergent selection
Angus cattle
Efficiency
Bulls
Identification
Tenderness
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Queensland Alliance for Agriculture and Food Innovation
Official 2014 Collection
 
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Citation counts: TR Web of Science Citation Count  Cited 12 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 11 times in Scopus Article | Citations
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