Genomic prediction for carcass traits in Japanese Black cattle considering mixed structure of subpopulations

  • ZODA Aoi
    Graduate School of Agriculture, Kyoto University
  • OGAWA Shinichiro
    Graduate School of Agriculture, Kyoto University Graduate School of Agricultural Science, Tohoku University
  • MATSUDA Hirokazu
    Graduate School of Agriculture, Kyoto University Wagyu Registry Association
  • TANIGUCHI Yukio
    Graduate School of Agriculture, Kyoto University
  • WATANABE Toshio
    National Livestock Breeding Center Maebashi Institute of Animal Science, Livestock Improvement Association of Japan
  • SUGIMOTO Yoshikazu
    Shirakawa Institute of Animal Genetics
  • WAISAKI Hiroaki
    Graduate School of Agriculture, Kyoto University Sado Island Center for Ecological Sustainability, Niigata University

Bibliographic Information

Other Title
  • 黒毛和種の集団構造を考慮に入れた枝肉形質に関するゲノミック予測

Search this article

Abstract

We performed Bayesian clustering analysis using STRUCTURE software with genotype data on 33,063 commercial single nucleotide polymorphism (SNP) markers in 4,348 Japanese Black fattened steers slaughtered at carcass markets in Tokyo, Osaka, Hyogo, Tottori, and Hiroshima prefectures. When the number of the assumed clusters in STRUCTURE was 2, the steers from Hyogo prefecture were clearly separated from the others. This indicates the usefulness of the STRUCTURE analysis with commercial SNP markers for the clarifications of the difference of the genetic constitutions of each prefecture. Next, genomic predictions for carcass traits were conducted using a statistical model including the proportions of the clusters as partial linear regressions. Genomic breeding values predicted by the model without the STRUCTURE covariates were likely to be divided into the part of explaining the STRUCTURE analysis and the remaining part. This result shows the possibility that the accuracy of genomic prediction depends on the degree of information of the genomic population structure.

Journal

Citations (1)*help

See more

References(41)*help

See more

Details 詳細情報について

Report a problem

Back to top