4.7 Article

Genomic versus phenotypic selection to improve corn borer resistance and grain yield in maize

Journal

FRONTIERS IN PLANT SCIENCE
Volume 14, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpls.2023.1162440

Keywords

maize; stem borer; resistance; yield; genomic selection; phenotypic selection

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The study compared genomic selection (GS) and phenotypic selection (PS) for improving resistance/tolerance to maize stem borers and yield. GS achieved the highest genetic gain for yield, while PS achieved the highest reduction in tunnel length but was ineffective for increasing yield. However, phenotypic or genomic selection for increased resistance may be more effective in improving both traits together, although the gains per cycle would be small for both traits.
IntroductionThe study of yield and resistance/tolerance to pest are related traits fundamental for maize breeding programs. Genomic selection (GS), which uses all marker information to calculate genomic breeding values, is presented as an emerging alternative to phenotypic and marker-assisted selections for improving complex traits controlled by many genes with small effects. Therefore, although phenotypic selection (PS) has been effective for increasing resistance and yield under high infestation with maize stem borers, higher genetic gains are expected to be obtained through GS based on the complex architecture of both traits. Our objective was to test whether GS is more effective than PS for improving resistance and/or tolerance to maize stem borers and grain yield. MethodsFor this, we compared different selection programs based on phenotype and genotypic value for a single trait, resistance or yield, and for both traits together. Results and discussionWe obtained that GS achieved the highest genetic gain for yield, meanwhile phenotypic selection for yield was the program that achieved the highest reduction of tunnel length, but was ineffective for increasing yield. However, phenotypic or genomic selection for increased resistance may be more effective in improving both traits together; although the gains per cycle would be small for both traits.

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