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Permanent link (DOI): https://doi.org/10.7939/R3G41Z

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Application of genetic markers for evaluation of residual feed intake in beef cattle Open Access

Descriptions

Other title
Subject/Keyword
SNP
markers
RFI
Beef
Genetic
Evaluation
Cattle
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Mujibi, Fidalis
Supervisor and department
Crews, Denny (Animal Science)
Moore, Stephen (Agricultural, Food and Nutritional Science)
Basarab, John (Alberta Agriculture and Rural Development)
Wang, Zhiquan (Agricultural, Food and Nutritional Science)
Examining committee member and department
Basarab, John (Alberta Agriculture and Rural Development)
Lin, Guohui (Computing Science)
Moore, Stephen (Agricultural, Food and Nutritional Science)
Dekkers, Jack (Animal Science)
Crews, Denny (Animal Science)
Wang, Zhiquan (Agricultural, Food and Nutritional Science)
Department
Department of Agricultural, Food and Nutritional Science
Specialization

Date accepted
2010-09-29T19:26:07Z
Graduation date
2010-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Improving feed efficiency has become a top priority in beef cattle production because of the rapidly increasing cost of feed provision. However, because of the expense associated with collecting individual animal feed intake data, only a relatively small number of animals have been tested, leading to low accuracies of estimated breeding values (EBV). Three studies were conducted to demonstrate the usefulness of including DNA marker information in RFI genetic evaluations. In the first study, the effect of period of testing on RFI was assessed. Beef cattle steers were tested for feed intake, with different cohorts tested in the fall-winter and winter-spring seasons. Seasonal differences were detected although these were confounded by differences in age and weight among the seasons. Additionally, mean EBV accuracy obtained was low, ranging between 0.47 and 0.51, implying that strategies to increase this accuracy are necessary. In the 2nd study, a suite of genetic markers predictive of RFI, DMI and ADG were pre-selected using single marker regression analysis and the top 100 SNPs analyzed further in 5 replicates of the training data to provide prediction equations for RFI, DMI and ADG. Cumulative marker phenotypes (CMP) were used to predict trait phenotypes and accuracy of prediction ranged between 0.007 and 0.414. Given that this prediction accuracy was lower than the polygenic EBV accuracy, the CMP would need to be combined with EBV for effective marker assisted selection. In study 3, genomic selection (GS) theory and methodology were used to derive genomic breeding values (GEBV) for RFI, DMI and ADG. The accuracy of prediction obtained with GEBV was low, ranging from 0.223 to 0.479 for marker panel with 200 SNPs, and 0.114 to 0.246 for a marker panel with 37,959 SNPs, depending on the GS method used. The results from these studies demonstrate that the utility of genetic markers for genomic prediction of RFI in beef cattle may be possible, but will likely be more effective if a tool that combines GEBV with traditional BLUP EBV is used for selection.
Language
English
DOI
doi:10.7939/R3G41Z
Rights
License granted by Fidalis Mujibi (fmujibi@ualberta.ca) on 2010-09-27T19:31:13Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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