Communication Dans Un Congrès Année : 2022

Improving genomic predictions with inbreeding and non-additive effects in two admixed maize hybrid populations in single and multi-environment contexts

Résumé

In maize (Zea mays), hybrid selection has led to the structuration of genetic diversity into complementary heterotic groups. This structuration is convenient for creating good performing hybrids but the reduced gene flow between groups increases the risk of intra-group genetic erosion associated with drift and selection, which may hinder long term breeding efficiency. It also complexifies the introduction of diversity from material such as landraces or admixed individuals derived from intergroup hybrids, that cannot be assigned to a specific heterotic group. Crossing admixed lines can generate contrasted levels of inbreeding in the hybrid population. This can reveal substantial non-additive effects, which impact performance and variation for traits showing heterosis These non-additive effects raise specific issues for the implementation of genomic selection. Recent methodological developments modelling inbreeding and non-additive effects with the natural and orthogonal interaction approach (NOIA) have been proposed in order to increase genomic prediction accuracy in hybrid populations. Using two maize populations of hybrids admixed between dent and flint heterotic groups, we compared genomic prediction models incorporating (or not) inbreeding and non-additive effects in single and multi-environment contexts. Both populations showed a strong impact of inbreeding on plant yield, height and flowering time, which was supported by the superiority of prediction models incorporating this effect. The model including additivity, dominance, epistasis and inbreeding effects appeared to be the most robust for prediction across traits and populations and was advantageous when predicting hybrids not observed yet in any environment. Overall, comparing variance decompositions was helpful to guide model selection for genomic prediction. Finally, we recommend the use of models including inbreeding and non-additive parameters following the NOIA approach to increase prediction accuracy in admixed populations. Based on these results we will discuss the opportunities offered by genomic selection to revisit maize hybrid breeding.

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Dates et versions

hal-04458027 , version 1 (14-02-2024)

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  • HAL Id : hal-04458027 , version 1

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Laurence Moreau, Morgane Roth, Aurélien Beugnot, Tristan Mary-Huard, Alain Charcosset, et al.. Improving genomic predictions with inbreeding and non-additive effects in two admixed maize hybrid populations in single and multi-environment contexts. XXVth EUCARPIA Maize and Sorghum Conference, May 2022, Belgrade, Serbia. ⟨hal-04458027⟩
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