Aug, 2017
Application of single-step genomic best linear unbiased prediction with a multiple-lactation random regression test-day model for Japanese Holsteins
ANIMAL SCIENCE JOURNAL
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- Volume
- 88
- Number
- 8
- First page
- 1226
- Last page
- 1231
- Language
- English
- Publishing type
- Research paper (scientific journal)
- DOI
- 10.1111/asj.12760
- Publisher
- WILEY
This study aimed to evaluate a validation reliability of single-step genomic best linear unbiased prediction (ssGBLUP) with a multiple-lactation random regression test-day model and investigate an effect of adding genotyped cows on the reliability. Two data sets for test-day records from the first three lactations were used: full data from February 1975 to December 2015 (60 850 534 records from 2 853 810 cows) and reduced data cut off in 2011 (53 091 066 records from 2 502 307 cows). We used marker genotypes of 4480 bulls and 608 cows. Genomic enhanced breeding values (GEBV) of 305-day milk yield in all the lactations were estimated for at least 535 young bulls using two marker data sets: bull genotypes only and both bulls and cows genotypes. The realized reliability (R-2) from linear regression analysis was used as an indicator of validation reliability. Using only genotyped bulls, R-2 was ranged from 0.41 to 0.46 and it was always higher than parent averages. The very similar R2 were observed when genotyped cows were added. An application of ssGBLUP to a multiple-lactation random regression model is feasible and adding a limited number of genotyped cows has no significant effect on reliability of GEBV for genotyped bulls.
- Link information
- ID information
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- DOI : 10.1111/asj.12760
- ISSN : 1344-3941
- eISSN : 1740-0929
- Web of Science ID : WOS:000408921700026