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Improving Selection Efficiency of Crop Breeding With Genomic Prediction Aided Sparse Phenotyping

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journal contribution
posted on 2021-11-05, 03:55 authored by S He, Y Jiang, R Thistlethwaite, Matthew HaydenMatthew Hayden, R Trethowan, Hans DaetwylerHans Daetwyler
Increasing the number of environments for phenotyping of crop lines in earlier stages of breeding programs can improve selection accuracy. However, this is often not feasible due to cost. In our study, we investigated a sparse phenotyping method that does not test all entries in all environments, but instead capitalizes on genomic prediction to predict missing phenotypes in additional environments without extra phenotyping expenditure. The breeders’ main interest – response to selection – was directly simulated to evaluate the effectiveness of the sparse genomic phenotyping method in a wheat and a rice data set. Whether sparse phenotyping resulted in more selection response depended on the correlations of phenotypes between environments. The sparse phenotyping method consistently showed statistically significant higher responses to selection, compared to complete phenotyping, when the majority of completely phenotyped environments were negatively (wheat) or lowly positively (rice) correlated and any extension environment was highly positively correlated with any of the completely phenotyped environments. When all environments were positively correlated (wheat) or any highly positively correlated environments existed (wheat and rice), sparse phenotyping did not improved response. Our results indicate that genomics-based sparse phenotyping can improve selection response in the middle stages of crop breeding programs.

Funding

This study is funded by the Grain Research Development Corporation (GRDC, US00081), the University of Sydney and Agriculture Victoria.

History

Publication Date

2021-10-06

Journal

Frontiers in Plant Science

Volume

12

Article Number

735285

Pagination

10p.

Publisher

Frontiers Media

ISSN

1664-462X

Rights Statement

© 2021 He, Jiang, Thistlethwaite, Hayden, Trethowan and Daetwyler. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.