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Boosting predictabilities of agronomic traits in rice using bivariate genomic selection

期刊

BRIEFINGS IN BIOINFORMATICS
卷 22, 期 3, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbaa103

关键词

bivariate; BLUP; genomic selection; HAT; predictability; metabolites

资金

  1. UC Riverside Faculty Startup Fund
  2. UC Riverside Hellman Fellowship
  3. UC Academic Senate Regents Faculty Fellowship
  4. Faculty Development Award
  5. UC Cancer Research Coordinating Committee Competition Award
  6. USDA NIFA [FACT 2019-67022-29930]

向作者/读者索取更多资源

In this study, a highly efficient bivariate genomic selection method was developed and demonstrated significant advantages over univariate methods in predicting traditional traits in rice. The incorporation of the HAT methodology in the 2D BLUP GS model increased computational efficiency by avoiding conventional cross-validation. Selected metabolites can further enhance predictability of traditional traits in the new 2D BLUP-HAT GS method.
The multivariate genomic selection (GS) models have not been adequately studied and their potential remains unclear. In this study, we developed a highly efficient bivariate (2D) GS method and demonstrated its significant advantages over the univariate (1D) rival methods using a rice dataset, where four traditional traits (i.e. yield, 1000-grain weight, grain number and tiller number) as well as 1000 metabolomic traits were analyzed. The novelty of the method is the incorporation of the HAT methodology in the 2D BLUP GS model such that the computational efficiency has been dramatically increased by avoiding the conventional cross-validation. The results indicated that (1) the 2D BLUP-HAT GS analysis generally produces higher predictabilities for two traits than those achieved by the analysis of individual traits using 1D GS model, and (2) selected metabolites may be utilized as ancillary traits in the new 2D BLUP-HAT GS method to further boost the predictability of traditional traits, especially for agronomically important traits with low 1D predictabilities.

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