AI Article Synopsis

  • Reciprocal recurrent genomic selection is a strategy designed to enhance hybrid wheat performance by leveraging two base populations.
  • The study developed predictive genomic equations using data from 1,604 wheat crosses, selecting 20 outstanding female lines to kickstart the selection program.
  • Results indicated a significant selection gain in grain yield after excluding two outlier environments, illustrating both the effectiveness of this breeding approach and the importance of refining predictive models.

Article Abstract

Reciprocal recurrent genomic selection is a breeding strategy aimed at improving the hybrid performance of two base populations. It promises to significantly advance hybrid breeding in wheat. Against this backdrop, the main objective of this study was to empirically investigate the potential and limitations of reciprocal recurrent genomic selection. Genome-wide predictive equations were developed using genomic and phenotypic data from a comprehensive population of 1,604 single crosses between 120 female and 15 male wheat lines. Twenty superior female lines were selected for initiation of the reciprocal recurrent genomic selection program. Focusing on the female pool, one cycle was performed with genomic selection steps at the F (60 out of 629 plants) and the F stage (49 out of 382 plants). Selection gain for grain yield was evaluated at six locations. Analyses of the phenotypic data showed pronounced genotype-by-environment interactions with two environments that formed an outgroup compared to the environments used for the genome-wide prediction equations. Removing these two environments for further analysis resulted in a selection gain of 1.0 dt ha compared to the hybrids of the original 20 parental lines. This underscores the potential of reciprocal recurrent genomic selection to promote hybrid wheat breeding, but also highlights the need to develop robust genome-wide predictive equations.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498042PMC
http://dx.doi.org/10.3389/fpls.2021.703419DOI Listing

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