BMC Genomics (Nov 2021)

Exploring the size of reference population for expected accuracy of genomic prediction using simulated and real data in Japanese Black cattle

  • Masayuki Takeda,
  • Keiichi Inoue,
  • Hidemi Oyama,
  • Katsuo Uchiyama,
  • Kanako Yoshinari,
  • Nanae Sasago,
  • Takatoshi Kojima,
  • Masashi Kashima,
  • Hiromi Suzuki,
  • Takehiro Kamata,
  • Masahiro Kumagai,
  • Wataru Takasugi,
  • Tatsuya Aonuma,
  • Yuusuke Soma,
  • Sachi Konno,
  • Takaaki Saito,
  • Mana Ishida,
  • Eiji Muraki,
  • Yoshinobu Inoue,
  • Megumi Takayama,
  • Shota Nariai,
  • Ryoya Hideshima,
  • Ryoichi Nakamura,
  • Sayuri Nishikawa,
  • Hiroshi Kobayashi,
  • Eri Shibata,
  • Koji Yamamoto,
  • Kenichi Yoshimura,
  • Hironori Matsuda,
  • Tetsuro Inoue,
  • Atsumi Fujita,
  • Shohei Terayama,
  • Kazuya Inoue,
  • Sayuri Morita,
  • Ryotaro Nakashima,
  • Ryohei Suezawa,
  • Takeshi Hanamure,
  • Atsushi Zoda,
  • Yoshinobu Uemoto

DOI
https://doi.org/10.1186/s12864-021-08121-z
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 11

Abstract

Read online

Abstract Background Size of reference population is a crucial factor affecting the accuracy of prediction of the genomic estimated breeding value (GEBV). There are few studies in beef cattle that have compared accuracies achieved using real data to that achieved with simulated data and deterministic predictions. Thus, extent to which traits of interest affect accuracy of genomic prediction in Japanese Black cattle remains obscure. This study aimed to explore the size of reference population for expected accuracy of genomic prediction for simulated and carcass traits in Japanese Black cattle using a large amount of samples. Results A simulation analysis showed that heritability and size of reference population substantially impacted the accuracy of GEBV, whereas the number of quantitative trait loci did not. The estimated numbers of independent chromosome segments (M e ) and the related weighting factor (w) derived from simulation results and a maximum likelihood (ML) approach were 1900–3900 and 1, respectively. The expected accuracy for trait with heritability of 0.1–0.5 fitted well with empirical values when the reference population comprised > 5000 animals. The heritability for carcass traits was estimated to be 0.29–0.41 and the accuracy of GEBVs was relatively consistent with simulation results. When the reference population comprised 7000–11,000 animals, the accuracy of GEBV for carcass traits can range 0.73–0.79, which is comparable to estimated breeding value obtained in the progeny test. Conclusion Our simulation analysis demonstrated that the expected accuracy of GEBV for a polygenic trait with low-to-moderate heritability could be practical in Japanese Black cattle population. For carcass traits, a total of 7000–11,000 animals can be a sufficient size of reference population for genomic prediction.

Keywords