論文

査読有り
2017年8月

Application of single-step genomic best linear unbiased prediction with a multiple-lactation random regression test-day model for Japanese Holsteins

ANIMAL SCIENCE JOURNAL
  • Toshimi Baba
  • ,
  • Yusaku Gotoh
  • ,
  • Satoshi Yamaguchi
  • ,
  • Satoshi Nakagawa
  • ,
  • Hayato Abe
  • ,
  • Yutaka Masuda
  • ,
  • Takayoshi Kawahara

88
8
開始ページ
1226
終了ページ
1231
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1111/asj.12760
出版者・発行元
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.

リンク情報
DOI
https://doi.org/10.1111/asj.12760
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000408921700026&DestApp=WOS_CPL
ID情報
  • DOI : 10.1111/asj.12760
  • ISSN : 1344-3941
  • eISSN : 1740-0929
  • Web of Science ID : WOS:000408921700026

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