摘要
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 2 nd 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.
摘要译文
提高饲料效率，已成为因进料供给的迅速增加成本肉牛生产的重中之重。但是，由于与收集个体动物饲料摄取数据相关的费用中，只有相对较少的动物已经过测试，导致估计育种值（EBV）的准确度低。三进行了研究，以证明包括RFI遗传评估DNA标记信息的有用性。在第一项研究中，对射频干扰的测试期间的效果进行了评估。肉牛肉牛进行了测试采食量，在秋季，冬季和冬春季节测试了不同组群。检测到季节性差异，虽然这些都是受季节之间的年龄和体重的差异混淆。此外，平均EBV准确性得到低，0.47和0.51之间不等，这意味着战略，以提高这一精度是必要的。在第2次研究中，一组遗传标记预测的RFI，DMI和ADG的采用单标记回归分析和顶端100的SNP预选进一步在5次重复的训练数据，以提供预测方程RFI，DMI和分析ADG。累积标记的表型（CMP）被用来预测性状表型和预测的准确性0.007和0.414之间不等。鉴于这一预测准确率比多基因EBV精度低，CMP将需要与EB病毒进行有效的标记辅助选择相结合。在研究中3，基因组选择（GS）的理论和方法被用来推导基因组育种值（GEBV）的RFI，DMI和ADG。与GEBV得到的预测的准确度低，范围从0.223至0.479对标记物组200个SNP，和0.114至0.246的标记物组与37959个SNP，根据所使用的GS方法。从这些研究的结果表明，遗传标记的RFI在肉牛基因组预测的效用是可能的，但如果它结合GEBV与传统BLUP EBV一工具用于选择将可能是更有效的。
Mujibi, Fidalis Denis Nagwalla. Application of genetic markers for evaluation of residual feed intake in beef cattle[D]. CA: University of Alberta (Canada), 2010