Estimation of genomic breeding values for residual feed intake in a multibreed cattle population

被引:33
|
作者
Khansefid, M. [1 ,2 ,3 ]
Pryce, J. E. [1 ,2 ]
Bolormaa, S. [1 ]
Miller, S. P. [4 ,5 ]
Wang, Z. [5 ]
Li, C. [5 ,6 ]
Goddard, M. E. [1 ,2 ,3 ]
机构
[1] AgriBio, Dept Environm & Primary Ind, Bundoora, Vic 3083, Australia
[2] AgriBio, Dairy Futures Cooperat Res Ctr CRC, Bundoora, Vic 3083, Australia
[3] Univ Melbourne, Melbourne Sch Land & Environm, Dept Agr & Food Syst, Parkville, Vic 3010, Australia
[4] Univ Guelph, Ctr Genet Improvement Livestock, Dept Anim & Poultry Sci, Guelph, ON N1G 2W0, Canada
[5] Univ Alberta, Livestock Gentec, Dept Agr Food & Nutr Sci, Edmonton, AB T6G 2C8, Canada
[6] Agr & Agri Food Canada, Lacombe Res Ctr, Lacombe, AB T4L 1W1, Canada
关键词
genomewide association study; genomic selection; multibreed; residual feed intake; BEEF-CATTLE; LINKAGE DISEQUILIBRIUM; ACCURACY; EFFICIENCY; ANGUS; DAIRY; PREDICTIONS; CHAROLAIS; HERITABILITY; SELECTION;
D O I
10.2527/jas.2014-7375
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Residual feed intake (RFI) is a measure of the efficiency of animals in feed utilization. The accuracies of GEBV for RFI could be improved by increasing the size of the reference population. Combining RFI records of different breeds is a way to do that. The aims of this study were to 1) develop a method for calculating GEBV in a multibreed population and 2) improve the accuracies of GEBV by using SNP associated with RFI. An alternative method for calculating accuracies of GEBV using genomic BLUP (GBLUP) equations is also described and compared to cross-validation tests. The dataset included RFI records and 606,096 SNP genotypes for 5,614 Bos taurus animals including 842 Holstein heifers and 2,009 Australian and 2,763 Canadian beef cattle. A range of models were tested for combining genotype and phenotype information from different breeds and the best model included an overall effect of each SNP, an effect of each SNP specific to a breed, and a small residual polygenic effect defined by the pedigree. In this model, the Holsteins and some Angus cattle were combined into 1 "breed class" because they were the only cattle measured for RFI at an early age (6-9 mo of age) and were fed a similar diet. The average empirical accuracy (0.31), estimated by calculating the correlation between GEBV and actual phenotypes divided by the square root of estimated heritability in 5-fold cross-validation tests, was near to that expected using the GBLUP equations (0.34). The average empirical and expected accuracies were 0.30 and 0.31, respectively, when the GEBV were estimated for each breed separately. Therefore, the across-breed reference population increased the accuracy of GEBV slightly, although the gain was greater for breeds with smaller number of individuals in the reference population (0.08 in Murray Grey and 0.11 in Hereford for empirical accuracy). In a second approach, SNP that were significantly (P < 0.001) associated with RFI in the beef cattle genomewide association studies were used to create an auxiliary genomic relationship matrix for estimating GEBV in Holstein heifers. The empirical (and expected) accuracy of GEBV within Holsteins increased from 0.33 (0.35) to 0.39 (0.36) and improved even more to 0.43 (0.50) when using a multibreed reference population. Therefore, a multibreed reference population is a useful resource to find SNP with a greater than average association with RFI in 1 breed and use them to estimate GEBV in another breed.
引用
收藏
页码:3270 / 3283
页数:14
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