論文

査読有り 責任著者
2020年

Simulation-based optimization of genomic selection scheme for accelerating genetic gain while preventing inbreeding depression in onion breeding

BREEDING SCIENCE
  • Daisuke Sekine
  • ,
  • Shiori Yabe

70
5
開始ページ
594
終了ページ
604
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1270/jsbbs.20047
出版者・発行元
JAPANESE SOC BREEDING

Genomic selection (GS) is being increasingly employed in plant breeding programs to accelerate genetic gain of economically important traits. However, its efficiency differs greatly across species, due to differences in reproduction and breeding strategies. Onion (Allium cepa L.) is an out-crossing crop but can be easily self-pollinated. High inbreeding depression occurs, and contamination of self-pollinated seeds is unavoidable in onion breeding. Taking this into consideration, 10-year breeding programs with and without GS were simulated. In addition to general GS, we proposed GS schemes to prevent inbreeding depression by avoiding coselection of close relatives and combining the shortening of generation time and updating of the prediction model. The results showed that general GS with shortening of generation time yielded the highest genetic gain among the selection schemes in early years. However, inbreeding increased rapidly, reaching very high levels in later years. The proposed GS combining shortening of generation time with updating of the prediction model was superior to the others in later years, as it yielded relatively high genetic gain while maintaining significantly low levels of inbreeding. These results suggested that GS can be beneficial in onion breeding, and an optimal scheme should be selected depending on the selection period.

リンク情報
DOI
https://doi.org/10.1270/jsbbs.20047
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000604260700011&DestApp=WOS_CPL
ID情報
  • DOI : 10.1270/jsbbs.20047
  • ISSN : 1344-7610
  • eISSN : 1347-3735
  • Web of Science ID : WOS:000604260700011

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